The Doctoral School in Medicine, Biomedical Science and Technology (2023)

Description: This five-module introduction course (in Danish) offers a comprehensive education and training program in clinical research for health care professionals, incl phd students. The five modules cover the followings topics: 1. Introduction to clinical research, 2. Methods, 3. Legal aspects (incl. data safety and GDPR) ethics, good clinical practice, and project management, 4. Oral and written research dissemination, and 5. Project economy and research funding.

Organizer: Centre for Clinical Research, North Denmark Regional Hospital

Lecturers: Senior clinicians and other health-related research professionals

ECTS: 2.0

Dates: March 28; May 8; June 12; August 22 and September 21 in 2023

Time: 8.00 AM – 3.30 PM

Place: The Skou Auditorium, North Denmark Regional Hospital

Zip code:  9800

City:  Hjoerring

Number of seats: In total 24 participants, including 6 PhD students and persons planning to be enrolled in a PhD program

Deadline: Tuesday 28^th of February 2023.

Important information concerning PhD courses: In conjunction with course the participants will be submitting an abstract to the annual Research Symposium (first Thursday in November) held at the North Denmark Regional Hospital.

Literature/Requirements: At individual level. A basic research textbook (Klinisk forskningsmetode) will be handed out to the course participants.

Registration:

Forskningskursus - Fra Idé til Projekt | Region Nordjylland (plan2learn.dk)

Description

This PhD course will be organized for the fifth time as a continuation of previous symposiums on physical activity and human performance. This year’s PhD course will also provide new knowledge related to the use of technologies for the assessment of physical performance among for instance youngsters and elderlies, trained or untrained adults. Lectures will cover measurement of human characteristics and capabilities, achievement of optimal efficiency, improvement of performance, technologies in sports and injury prevention in sports and at work.

This course will provide the audience with recent findings in sport sciences in a broad sense covering physical activity during leisure time and at work. Internationally recognized speakers as well as speakers from Aalborg University will be invited. The addressed topics will include for neuromechanics, motor control, biomechanics, ergonomics, exercise physiology, telerehabilitation (programs and technologies) as well as modelling.

A special emphasis will be given on the speakers-student interaction. The detailed agenda of the course will be provided on the course web site in due time. It will be possible to follow the PhD course remotely (all lectures will also be transmitted online).

Literature
A reading list with relevant papers and book chapters will be announced before the course.

Prerequisites
The students participating to this course should have basic knowledge on anatomy, physiology, and methods to assess human performance by means of quantitative methods.

Evaluation
Evaluation will be announced at the course.

Organizer:                    Professor Pascal Madeleine, email: pm@hst.aau.dk

Co-organisers:             Professor Birthe Dinesen, Associate Professor Jesper Franch, Associate Professor Mark de Zee, Associate Professor Mathias Vedsø Kristiansen, Associate Professor Rogerio Pessoto Hirata, Associate Professor Ryan Godsk Larsen, Professor Uwe Kersting  

Lecturers:                      Organisers, invited national and international speakers and speakers from the Dept. of Health Science and Technology and Aalborg University Hospital

ECTS:                              1.5

Date:                              1 and 2 June 2023 (8:15-16:15)

Place:                             Aalborg University

Deadline:                      11 May 2023              

Program:                       HES – mandatory course (also relevant for BEN, CPM)

Face to face and online lectures

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Couse name: Disease-related malnutrition

PhD Programme: Clinical Science and Laboratory and Translational Medicine

Description: This PhD course aims at providing thorough, reflective, and reflexive knowledge on the overall aspects of disease related malnutrition and is especially intended for students with clinical projects. Moreover, this course aims to meet students’ needs in addition to covering essential elements of clinical research and evidence-based practice. Additionally, the course will attend especially to the issue of translational nutrition from the more cell based experimental nutrition over clinical nutrition to applied research methods. Prerequisites:

Students enrolled in PhD program and at a point where they have finished their general courses. Students doing quantitative and mixed method research in nutrition, regardless of research setting, are encouraged to apply for this course

Learning objectives. After the course the students should be able to: Explain the scientific basis and relevance and relevance of disease related malnutrition. Decide on scientific approaches and methodologies special for clinical nutrition research.

Teaching methods: This course will be run in a combined lecture and workshop style and the students will be encouraged to active participation.

Organizer:  Mette Holst, Professor, Head of Research, PhD. Centre for Nutrition and intestinal Failure, Aalborg University hospital and Department of Clinical Medicine, Aalborg University

Lecturers: Henrik Højgaard Rasmussen, Professor, Consultant, MD, PhD. Centre for Nutrition and intestinal Failure, Aalborg University hospital and Department of Clinical Medicine, Aalborg University

Randi Tobberup, Head of Dietetics, PhD. Centre for Nutrition and intestinal Failure, Aalborg University hospital

Helle Nygaard Lærke, Senior researcher, PhD. Aarhus University

Mette Holst, Professor, Head of Research, PhD. Centre for Nutrition and intestinal Failure, Aalborg University hospital and Department of Clinical Medicine, Aalborg University

ECTS: 2

Dates: 30, 31 October and 1 and 2 November
Time: 9-16

Place: 

Zip code:  9000

City:  Aalborg

Number of seats: 20

Deadline: 1 September 2023

Important information concerning PhD courses: Criteria for assessment: Active participation in the course including brief presentation of own project and ‘methodology challenge you wish to tackle’. Presence at least three out of four days.

Online participation is not offered.

Literature/Requirements: Chapters from: Sobotka L et al. “Basics in Clinical Nutrition” Fifth. Ed. Publishing House Galèn,  ISBN978-80-7492-427-9 and other literature will follow upon signing for the course.

Program:

Day 1

Welcome and introduction

Background and definitions.

Metabolism in healthy individuals, fasting and disease.

Nutritional assessment; Body composition and function (l)

Assessment of skeletal muscle mass, BIA, CT and MR

Anthropometric measures

Measures of physical function

Practical workshop

Nutritional intake in the diagnosis of malnutrition

Day 2

Nutritional Assessment (ll)

Bowel anatomy and function

Measurement of absorption and malabsorption

The role of the gut microbiota in inflammation and metabolism

Laboratory analysis and biomarkers in nutrition and inflammation

Day 3

Nutritional assessment (lll)

Nutrition Impact Symptoms (NIS) and their implications on nutrition intake

NIS assessment methods for use in clinical practice and research

Patient reported outcome measures  (PROMS) for use in clinical practice and research

Nutritional treatment

Estimation and measurements of nutritional requirements in different phenotypes

Targeted nutritional therapy

1)      Generalized interventions and specific therapies aimed at inflammation and body composition

2)      Specific nutrients and bioactive substances targeting anabolism and inflammation

Nutrition intervention methods; Oral, enteral and parenteral

Methods for quantifying nutrition intake

Day 4

Relevant clinical outcomes in clinical nutrition

Research methods in clinical nutrition

Experimental and clinical research designs

1)                         Experimental: Laboratory tests, animal models, surrogate markers and power calculation

2)                         Clinical: Observational and intervention studies

3)                         Applied: Questionnaires, qualitative methods and implementation studies

Workshops will be included during the day

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Qualitative research within health science

Description: The use of qualitative research and data within the health sciences has been increasing over the last 20 years. Either as the main source of data, or as part of a mixed methods design where qualitative and quantitative studies supplement each other. This course will provide participants´ with basis competences in designing a qualitative study and experiences on benefits and limitations when using qualitative methods within the health sciences. The specific focus will be on designing the study, choosing appropriate methods, collecting data and finally analysing the data.

The detailed agenda of the course will be provided on the course web site.

The course will be a three and a half day course and the main topics will include:

• What characterises qualitative research and why should you choose a qualitative approach
• Introduction to different qualitative methods and their possibilities and limitations when used within the health sciences
• Introduction to analytical strategies
• How to work with and analyse ethical implications in qualitative research

Literature: Selected papers and book chapters will be announced to the participants in appropriate time before the course via Moodle.

Prerequisites: The course targets Ph.D. students working within the areas of health science, who are planning to conduct qualitative research as part of their Ph.D, or are interested in gaining knowledge about the use of qualitative methods.

Evaluation: Will be announced in appropriate time before the course.

Organizer: Associate Professor Henrik Vardinghus-Nielsen, Department of Health Science and Technology, Aalborg University.

Lecturers: Associate Professor Henrik Vardinghus-Nielsen, Associate Professor Kirsten Schultz Petersen, Associate Professor Helle Lønstrup Haslund-Thomsen and Associate Professor Jane Andreasen

ECTS: 3

Dates: 12-15 June 2023

Time:
Monday – Wednesday from 9.00 to 16.00
Thursday from 9.00 to 13.00

Place:  Aalborg University - course rooms will be informed later

Deadline: 5. June 2023

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Description

This two-day course is offered in a collaboration between Aalborg University and the Centre for Development, Evaluation, Complexity and Implementation in Public Health Improvement (DECIPHer), Cardiff University, UK – a Public Health Research Centre of Excellence.

The British Medical Research Council’s (MRC) framework for development and evaluation of complex interventions are increasingly used world-wide to improve the quality of interventions in public health and applied health sciences.

This course will introduce participants to the 2021 MRC framework, the role of program theory in intervention research and some of the guidance underlying the overall 2021 MRC framework: the 2020 guidance on adaption of interventions to other contexts (ADAPT) and the 2015 guidance on Process evaluation.

In intervention research, most attention are often given to the theoretical and methodological issues of intervention development and to the design of appropriate effect evaluation, often by use of randomised controlled trials.

Understanding change mechanisms and knowing when and how to adapt an evidence-based intervention instead of starting a new development process is however an highly important aspects of work with complex interventions. And also process evaluation is an essential part of testing and evaluation of complex interventions, allowing researchers to learn the significance of context and mechanisms of impact - how the delivered interventions do (or doesn’t) bring about change. 

·         The course will provide the participants with a working knowledge of the theory and practice of adaption and process
          evaluation of interventions in complex systems, focusing on:

·         Program theory and logic modelling in interventions in complex systems

·         The concept of adaption and key issues in adaption processes

·         Stakeholder involvement and other key elements in the 2021 MRC framework

·         The role of process evaluation in understanding interventions in complex systems

·         Evaluation questions and process evaluation methods

·         Analysis and dissemination of process evaluation data

During the course, lectures will be mixed with group work and discussions

Literature 

Selected international, scientific papers as well as book chapters

Evaluation

Active participation and completion of course exercises

Organizer:          Associate professor Charlotte Overgaard; e-mail: co@hst.aau.dk

Lecturers:           Senior Lecturer, Dr. Rhiannon Evans, Research Associate, Dr. Rachael Brown, Associate professor,
                            Dr. Kirsten Schultz Petersen, Associate professor, Dr. Charlotte Overgaard

ECTS:                   2.0            

Place:                   Aalborg University.

Program:             HCHPO

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Couse name: CLINICAL SCIENCE, LABORATORY AND TRANSLATIONAL MEDICINE - INTRO-COURSE 2023.

PhD Programme: CLINICAL SCIENCE, LABORATORY AND TRANSLATIONAL MEDICINE

Description: An introduction to being a PhD-student in this programme. Basic information on how to handle samples for biochemical analyses and other diagnostic investigations. How to establish a clinical study; use of databases; need of various approvals; basic statistics.

This course is mandatory for students at the programme.

Organizer: Head of the programme Søren Risom Kristensen

Lecturers: Mainly supervisors/older PhD-students in the programme

ECTS: 1.0

Dates:    17 April 2023

Time: One day course

Place: Forskningens Hus, Aalborg Universitetshospital

Zip code:  9000

City:  Aalborg

Number of seats: 

Deadline:    24 March 2023

Important information concerning PhD courses:

Literature/Requirements

Description

Omics technologies including genomics, transcriptomics, epigenetics, proteomics and metabolomics are now key technologies in multiple fields of research and a highly active domain in health and medical investigation. Omics is an interdisciplinary research field that coalesces researchers from many different areas of biomedical research into one of the most likely disciplines to successfully foster the translation of basic scientific knowledge into clinical applications for the benefit of patients.

This PhD course will focus on advanced theoretical and practical aspects of Omics strategies in Life & Medical sciences. Our focus will address the clinical study design and ethical protol requirements to application of omics strategies to address a diverse range of medical pathologies, including but not limited to autoimmune disorders, diseases associated to neuro-inflammation and neurodegeneration as well as chronic pain conditions. Omics are currently utilized extensively to identify biomarker patterns for detection of disease risk, patient’s stratification, identification of responders to a particular treatment, or elucidation of mechanism of disease or drug action with ultimate goal of patient safety and better health outcome.

The course will be a combination of lectures, bioinformatics tutorials and laboratory demonstrations with hands-on experimental parts. Considering the value and importance of omics, and a rapidly growing trend, this course aims at providing front edge information about current advanced methodologies applied in medical omics through real-life examples. Hence, participants will be able to translate the presented strategies and methods into their own health, and medical related research.

Lectures & Practical

·       Clinical study design and ethical aspects for Omics type projects

·       Sample handling from patients (biobank), animal models, or in-vitro systems to the mass spectrometer and beyond

·       Theoretical and strategic introduction to Omics technologies in scope of clinical research.

·       Strategies for clinical proteomics, genomics and metabolomics for personalized medicine in several fields including autoimmune disorders, neurodegenerative diseases and chronic pain.

·       Applications for quantitative proteomics and metabolomics in health and medical science.

·       Statistical evaluation and presentations of Omics data in scientific publications

·       Bioinformatice processing and data integration of Omics data

·       Practical session – From biofluid to quantitative proteomics analysis.

Literature

Notes, literature and exercise instruction will be distributed at the course

Prerequisites

None; Background in clinical, translational or biomedical sciences is recommended.

Evaluation Active participation in the theoretical and experimental course.

Organizer:         Associate professor Allan Stensballe, email: as@hst.aau.dk

Lecturers:          Associate Professor Allan Stensballe; Aalborg University, Christopher Aboo; invited lectures.

ECTS:                  2.5

Dates:                 3., 4., 5. april 2023 Approx 8-16;

                           25., 26. and 27. September 2023

Format:              Lectures (on-site); Laboratory execises (Approx 3x2hours on-site)

Place:                  Aalborg University

Deadline:           4 September 2023

Number of seats: 18

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Overdiagnosis. Sick, healthy, or in-between

Medical technology is vastly expanding, and self-assessment has become a big part of being healthy. Alongside, population screening is emerging, and diagnostic thresholds change, which means that even small deviations from “the normal” will be categorized as diseases. At the same time, new diseases emerge, and owing to this, increased numbers of treatments and check-ups will be needed.

This PhD course provides an overview of overdiagnosis, overdetection, misdiagnosis, and overtreatment, and following that, causes, drivers, mechanisms, and incentives to overdiagnosis.

The topics will include

·       Overdiagnosis. What it is and what it isn´t.

·       Health culture and the quest for avoiding diseases and death

·       What is the diagnostic accuracy of a test when overdiagnosis occurs?

·       Self-monitoring and” digital health”

The course will be based on short lectures, group discussions, cases from epidemiological and qualitative studies, and analyzing and scrutinizing study designs.

The attendees will gain competences into the design and interpretation of clinical research beyond the Baysian diagnostic paradigm of a simple 2x2 table. In addition, they will get a perspective on how digital self-monitoring will change the culture and concept of health and disease.

The PhD course will be of interest to any researcher working with clinical research, digital health, diagnostics, screening, population-based research, and epidemiology.

Organizer: Associate Professor, Niels Holmark Andersen, n.holmark@rn.dk

Lecturers: Associate Professor Alexandra Brandt Ryborg Jønsson & Professor John Brandt Brodersen

ECTS: 1,5

Dates:  TBD

Time: 8.30 – 15.30

Deadline: 2.3.2023

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Couse name: Development and implementation of machine learning models for dynamic risk prediction models in health care applications (2023)

PhD Program: Medicine, Biomedical Science and Technology

Description (preliminary):

Traditional risk prediction generates a risk estimate at a defined timepoint in a patient’s disease trajectory, for example the risk of death within 30 days following a surgical procedure. In contrast, dynamic risk prediction enables prediction of risk at any time point. This allows to continuously monitor a patient’s risk profile and forms the basis for intervention if the predicted risk increases. In this course, we will explore methodological and technical solutions, as well as corresponding challenges, for developing and implementing such solutions in health care. The course includes the following topics:

1) Data management: This part of the course considers the challenges of preparing heterogenous longitudinal health data for prediction. We will cover the various steps involved in this process, including data formatting, feature engineering, and splitting strategies for model validation. This will include discussion about how to handle irregularly sampled health data, data leakage, class imbalance, temporal robustness, normalization, and other potential biases.

2) Modelling: In this part of the course, participants will be led through the process of building such models. We will introduce both basic and more advanced dynamic machine learning prediction algorithms, such as gradient tree boosting, random forest, and LSTM and discuss issues related to performance metrics and hyperparameter optimization, for example Bayesian optimization.

3) Implementation: In the last part of the course, we will consider the challenges associated with the implementation of predictive tools in the clinic. This includes technical aspects about hosting, user interface, and access to live data, including an introduction to the FHIR standard. Regulatory and organizational issues will also be discussed. During the project the participants will get hands on experience covering realistic scenarios related to the subjects discussed. This will include data management of representative data sets, training models and hands on introduction to the FHIR set-up.

Organizers: 

Heidi Søgaard Christensen, Postdoc, Center for Molecular Prediction in Inflammatory Bowel Disease, Department of Clinical Medicine, hschr@dcm.aau.dk

Charles Vesteghem, Assistant Professor, Center for Clinical Data Science and Center for Molecular Prediction in Inflammatory Bowel Disease, Department of Clinical Medicine, AAU, cvesteghem@dcm.aau.dk 

Martin Bøgsted, Professor, Center for Molecular Prediction in Inflammatory Bowel Disease, Department of Clinical Medicine and Center for Clinical Data Science, Department of Clinical Medicine, m_boegsted@dcm.aau.dk

Lecturers (preliminary): 

Heidi Søgaard Christensen, Postdoc, Center for Molecular Prediction in Inflammatory Bowel Disease, Department of Clinical Medicine, AAU

Anne Krogh Nøhr, Postdoc, Charles Vesteghem, Assistant Professor, Rasmus Froberg Brøndum, Associate Professor, Center for Clinical Data Science and Center for Molecular Prediction in Inflammatory Bowel Disease, Department of Clinical Medicine, AAU

Ida Burchardt Egendal, PhD Student, Simon Christian Dahl, Senior Software Developer, Center for Clinical Data Science, Department of Clinical Medicine, AAU

More TBA.

ECTS: 3

Dates: June 13 – June 16, 2023 (4 days)

Time: 8:30 – 16:00

Place: 13 June, room 12.02.066

Zip code:  9220

City:  Aalborg Ø

Number of seats: 30

Deadline: 2022-05-29

Important information concerning PhD courses:
Literature/Requirements:

The participants are expected to have basic knowledge on regression analysis as well as programming experience in a statistical software tool, such as R or Python. The workshop will be held using Python and limited support will be provided for other programming languages.

Tomašev, N. et al. Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records. Nature Protocols (2021) doi:10.1038/s41596-021-00513-5.

Vesteghem, C. et al. Dynamic risk prediction of 30-day mortality in patients with advanced lung cancer: Comparing five machine learning approaches. JCO CCI (2022) doi:10.1016/j.clon.2022.03.015

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Couse name: Validation of prediction models in epidemiology and medicine 2023

PhD Program: Epidemiology and Biostatistics

Description: While most medical studies aim to explain some phenomenon, a significant proportion does not have this as a primary goal. These studies instead aim to predict a certain event or measure as accurately as possible given a number of predictors. Although explaining and predicting are two separate goals, they are often interchanged in medical studies. More importantly, the statistical approaches used for these two types of data analyses are not the same. The course covers the following topics:

1. The basic differences between explanatory and predictive studies.
2. Model estimation: variable selection, variable predictive power and penalisation.
3. Model Performance: N-fold cross validation, geographical and temporal validation, external validation.
4. Model validity: Calibration and calibration slope, receiver operating characteristic (ROC) curve incl. area under the curve (AUC), Bland-Altman plots, prediction intervals and decision analysis.
5. Examples from the scientific literature.

Upon completion of the course, the student will be able to distinguish between predictive and explanatory data analyses, as well as understand the basic statistical tools used in predictive studies.

Students will be evaluated based on an assignment with oral presentation in groups of 2-4 participants

Organizer: Lasse Hjort Jakobsen (lasse.j@rn.dk), Jan Brink Valentin (jvalentin@dcm.aau.dk)

Lecturers: Lasse Hjort Jakobsen, Jan Brink Valentin, Simon Grøntved

ECTS: 2.5

Dates: 24, 25, 26, 27 April 2023

Time: 08.30 to 16.00

Place: Selma Lagerløfs Vej 249, room 11.00.032

Zip code: 9260

City: Gistrup

Number of seats: 40

Deadline: 1 April 2023

Important information concerning PhD courses: None

Literature:

Moons K, Royston P, Vergouwe Y, Grobbee D, Altman D. Prognosis and prognostic research: what, why and how? BMJ2008;b375.

Ewout W. Steyerberg, Yvonne Vergouwe; Towards better clinical prediction models: seven steps for development and an ABCD for validation, European Heart Journal, Volume 35, Issue 29, 1 August 2014, Pages 1925–1931, https://doi.org/10.1093/eurheartj/ehu207

Requirements: Basic Statistics and basic programming abilities with Stata or R, all participants must bring a laptop with either Stata or R installed.

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Description: One of modern biology’s biggest surprises was the finding that the human genome contains only about 20,000 protein-coding genes, comprising less than 2% of the genome sequence. However, recent data imply that the human genome is pervasively transcribed and encodes tens of thousands of non-protein coding RNAs (ncRNAs) that play critical regulatory roles in numerous biological processes. These ncRNAs include over 2,300 microRNAs (miRNAs), a set of structural RNAs [such as ribosomal RNAs (rRNAs), transfer RNAs (tRNAs), and small nuclear RNAs (snRNAs)], and at least 50,000 long noncoding RNAs (lncRNAs). An improved understanding of basic RNA biology and the complexity of the human transcriptome has triggered a corresponding revolution in development of RNA-based therapies, which hold promise for the treatment of a wide range of life-threatening diseases. This is highlighted by the recent FDA approvals of three RNA medicines: (i) the antisense oligonucleotide (ASO)-based drugs eteplirsen for treatment of Duchenne muscular dystrophy and (ii) nusinersen for treatment of the neurodegenerative disease spinal muscular atrophy, respectively, and (iii) the siRNA drug patisiran for the treatment of hereditary transthyretin amyloidosis with polyneuropathy. Notably, RNA drugs can be designed to target essentially any RNA transcript encoded by the genome and can thus target a large part of the currently undruggable genome.

This PhD course will provide the participants with an overview of ncRNA biology and development of RNA-targeted therapeutics and consists of a series of research seminars and laboratory exercises. The seminars will cover key topics in the rapidly expanding field of RNA research from ncRNA biology, high-throughput RNA sequencing (RNA-seq) methods and bioinformatics/computational analysis of RNA-seq data to the emerging roles of ncRNAs in human disease and development of RNA-based medicines. Each seminar will be followed by a scientific discussion of the participating PhD students with the lecturer. As preparation, two scientific papers selected by the lecturer have to be read prior to the PhD course. The laboratory exercises are designed to provide hands-on experience with key methods and tools used in ncRNA research and discovery of RNA-targeted therapeutics.

Literature:

1. Khvorova A & Watts JK. The chemical evolution of oligonucleotide therapies of clinical utility. Nat. Biotechnol. 35: 238–248 (2017).
2. Lim KR, Maruyama R & Yokota T. Eteplirsen in the treatment of Duchenne muscular dystrophy. Drug Des Devel Ther. 11: 533-545 (2017).
3. Corey, DR. 2017. Nusinersen, an antisense oligonucleotide drug for spinal muscular atrophy. Nat Neurosci. 20: 497–499 (2017).
4. Setten RL, Rossi JJ & Han SP. The current state and future directions of RNAi-based therapeutics. Nat Rev Drug Discov. 18: 421-446 (2019).

Prerequisites: PhD students in biomedical research or molecular biology with an interest in ncRNA biology in human health and disease and discovery and development of RNA-targeted therapeutics should apply.

Evaluation: Participants who have engaged actively in all parts of the course and completed all lab exercises satisfactorily will be awarded a certificate of completion at the end of the PhD course. The workload corresponds to 5 ECTS points and includes one week of preparation prior to the course (two articles for each lecture that should be read in advance).

Description

Case facilitation with problem-based learning (PBL) is the central teaching model at Aalborg University Medicine and Medicine with industrial specialization (MedIS).

The aim of problem-based learning is to facilitate learning in ways that mirror the professional practice. This has several advantages, including highlighting the applicability of the material being taught and facilitate active learning, which increases student motivation, engagement, and the final learning outcome.

A feature of problem-based case work is the use of problem triggers placed in a context, e.g. a medical phenomenon. Small groups of students work on the case together: 1) They analyse the problem, 2) identify learning issues for developing an adequate explanation for the phenomenon, 3) follow up with research, and 4) prepare the explanations. When required, they would also determine the course of treatment, action or solution that best address the phenomenon. Focus is on analyzing complex situations with limited information using acquired knowledge and deduction, and learning to understand causalities of biological systems, i.e., the link between symptoms, biological mechanism, clinical outcomes, and applied treatments.

In this way, not only do the students gain knowledge about professional practice, the also come into the mindset of a professional presented with a context to deal with. (Barrows & Tamblyn, 1980)

The case facilitator has a central role in ensuring the optimal outcome of the case-sessions and can “make or break” the sessions. However, the teaching strategy of the case facilitator is vastly different from the role undertaken by a lecturer. Participants on this course will be given a solid introduction to the theoretical and practical foundation of case facilitation. A special focus is on the role of the case facilitator, and the practicalities of case facilitation, down to the level of what to bring to a session and other experiences. A simulated case session will demonstrate the role of the case facilitator.

Contents of lectures:

·       Introduction and theoretical foundation of problem-based case work

·       The important role of the case facilitator and the steps of case start and case end facilitation

·       Hands-on: Solve case under supervision

·       Case facilitator preparation for case sessions

·       Good and bad cases, how to edit and make new cases, and future directions of case work

Literature

Notes, literature, and exercise instruction will be distributed at the course

Prerequisites

None. The course will provide a solid foundation of case work but may also serve as a brush-up course.

Evaluation
Participants are expected to be active during the sessions and exercises.

Description

The course has a focus on disseminating the most relevant and recent achievements within biomedical and engineering science to address relevant health care problems. This course will be organized annually and will include a series of lectures from internationally recognized speakers and from speakers from Aalborg University that are experts within the field. During the symposium, some time will be dedicated to the facilitation of interaction between the speakers and participants. The detailed agenda of the course will be provided on the course web site. Main topics can include electrophysiology, psychophysics, bio-signal processing, biostatistics, rehabilitation technology, machine learning, physiological modeling, decision support, big data, image analysis and computational neuroscience but also topics relevant for the life as a PhD student such as management of a research project, risk analysis and mitigation etc.

Literature

Relevant journal articles and book chapters related to the specific talks will be announced shortly before the course.

Prerequisites

The course targets PhD students of the Program in Biomedical Engineering and Neuroscience and other PhD students working within these areas. The course is repeated every year with a different focus, thus participation to the previous edition does not preclude participation in this edition.

Evaluation

A poster session will be organized during the symposium. PhD students will bring and present a poster on their own work (it is allowed to bring a poster presented at another conference or meeting).

Organiser:         Associate Professor Sabata Gervasio, email: saba@hst.aau.dk

Lecturers:          Invited lecturers and lecturers from Department of Health Science and Technology and Clinical Medicine

ECTS:                  1.5

Dates:                 7 and 8 December 2023 (08:15-16:15)

Place:                  Aalborg University

Deadline:           16 November 2023              

Program:            BEN – mandatory course (also relevant for HES, CSLTM, CPM)

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Description

The course will focus on the importance of method comparison studies when evaluating new clinical and experimental methods. The course will describe how method comparison studies are designed and how obtained results are analysed and described. Application of analytical measures such as Coefficient of Variance, Intra-Class Correlation, differences in means, and Bland-Altman’s limits of agreement, inter-rater reliability, test accuracy and sample size estimation will be discussed. The aim of the course is to provide the participants with a toolbox that enables them to perform and analyse method comparison studies. This advanced course in biostatistics assumes knowledge of basic methods in biostatistics, including the concepts of hypothesis testing, and basic study designs. The course is designed for researchers working in both clinical and experimental settings.

Literature

·       Atkinson G, Nevill A. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine.  Sports Med 1998; 26: 217-238,

·       Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. Journal of Strength and Conditioning Research 2005; 19: 231–240

·       Bland JM, Altman DG. Measuring agreement in method comparison studies. Statistical Methods in Medical Research 1999; 8: 135 – 160

and links, datasets and handouts distributed prior to and during the course.

Prerequisites

Basic knowledge on statistics (e.g., Biostatistics I)

Evaluation:        Short project/assignment

Description

The course will be conducted online

Research on biomedical engineering topics usually require the acquisition of biological signals or additional instrumentation that provides continuous time series. For non-engineers, processing those types of data can be time consuming and inaccurate if proper processing methods are not used. Therefore, the goal of this course is to present basic processing tools to analyse biological and non-biological signals.

The course is based on Matlab, one of the most powerful software packages for data recording and analysis in Engineering. The course presents a dynamic format, in which students will have practical experiences regarding the use of Matlab during the lectures. Students will be able to learn Matlab programming by accessing basic instructions through video contents recorded by the lecturer. Moreover, some specific tasks and exercises will be performed in the presence of the lecturer.

This format will offer to students the unique possibility to learn how to perform basic and complex operations with the assistant of the lecturer while generating the data analyses scripts. The course has been designed for PhD students without previous experience on programming on Matlab, such as physiotherapists, medical doctors, pharmacists, psychologists, sports science professionals. The ultimate goal of this PhD course is to provide students with basic yet reliable tools to process data for their own PhD projects.

The course will be divided in four modules

·         Introduction: basic operations and file management (importing, loading, saving files)

·         Data visualization, matrix manipulation

·         Code optimization: reducing processing time and minimizing changes of errors

·         Multi-subject dataset management and basic statistics

 Literature

To be announced. Readings will be provided via the course webpage.

Prerequisites

This course is ideal at students early or midway in their PhD. You should be at least 3 months into your project development. Ideally, students should use their own target data to develop scripts for analysis.

Evaluation

Assignment: Students must present a data analysis pipeline generated using Matlab on the last lecture day. The data should be preferably related to the topic of the PhD project, therefore benefiting the student in the standardization of data processing methods. Detailed explanations of the processing steps and the choices for data analysis, based on appropriate references, should be addressed in the presentation.

Organiser:        Associate Professor Anderson Oliveira, e-mail: oliveira@mp.aau.dk

Lecturer:           Associate Professor Anderson Oliveira, Aalborg University

ECTS:                  3.0

Dates:                2, 9, 16, 25, 30 May and 13 June 2023 (12:30-16:15)

Place:                 Aalborg University, Selma Lagerløfs Vej 249, 9260 Gistrup, room SLV 249/11.00.032

Deadline:         12 April 2023

Programs:        BEN (also relevant for HES, CPM, EB, B)

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

ASSESSMENT AND MODULATION OF PAIN MECHANISMS - A THEORETICAL AND HANDS-ON COURSE

Description

“Personalized Mechanistic Pain Medicine” aims to assess the underlying mechanisms of pain and target these mechanisms using tailored treatment. Assessment of pain is complex and range from assessments of nerve activity using advanced neurophysiological tests to patient reported outcomes. Emerging evidence supports that multiple pain mechanisms interact on each other and many of these are modulated by comorbidities and/or demographic features (such as age, gender, BMI).

This course will provide the students with an in-depth understanding of a range of pain mechanisms in relation to (1) central pain mechanisms using quantitative sensory testing; (2) assessments of cognitive factors (such as pain catastrophizing, anxiety and depression); and (3) neurophysiological assessments and modulation of the motor system and how this is related to changes in pain.

Students will be introduced to how these can be assessed and be provided with examples on and how these can be modulated. Additionally, this course includes an introduction to the pain laboratories and hands-on experience with assessments of pain mechanisms.

Literature

Selected papers and book chapters will be announced to the participants shortly before the course.

Prerequisites

None

Evaluation

A multiple-choice test will evaluate the student’s outcome of the course and evaluated as pass/not pass.

Organiser:          Associate Professor Kristian Kjær Petersen, email: kkp@hst.aau.dk

Lecturers:           Associate Professor Kristian Kjær Petersen, Assistant Professor Dennis Boye Larsen, Associate Professor Laura Petrini

ECTS:                     2.0

Dates:                   8, 9 10 March 2023 (08:15-16:15)

Place:                   Aalborg University, Selma Lagerløfs Vej 249, 9260 Gistrup

                             8 March: Room SLV 249/11.00.033

                             9 and 10 March: Room SLV 12.02.066

Deadline:            15 February 2023                     

Program:             BEN (relevant for all PhD students working with pain in humans)

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

ADVANCED PHYSIOLOGICAL MODELLING

Description

Modelling of physiological processes and tissues is a valuable tool in both research and industry. Modeling can give insights that can be difficult or even impossible to obtain using experimental methods. Such modelling can lead to a better understanding of physiological processes and, furthermore, it can help reduce the amount of experimental work needed in both research and development. As computational power is increasing, more advanced models can be solved using standard laptop computers. This allows more refined investigations as well as optimizing existing models. When using models it is essential to ensure validity of the models, either by experimental validation or comparison to reference values and data. Furthermore, when doing physiological modelling there are a number of potential pitfalls which has to be taken into account, considering for example selection and implementation of the appropriate numerical minimization algorithm.

This course introduces a number of generic modeling principles and addresses specific methods, ranging from identifiability analysis, model complexity, and parameter estimation to numerical solutions, which may be applied in your own research. The course also focuses on ensuring validity of the applied models. Through this course you will be introduced to and gain experience using the finite element method, which can be used to model a large variety of different physics such as force/strength/strain/displacement; heat transfer; electric transfer. You will gain knowledge and experience using compartmental models, typically used to study kinetics of materials in physiological systems from a whole-body perspective to the cellular level. Finally, you will gain insight into modelling excitable membranes, e.g. the modeling of the excitable membrane found in nerves, muscle fibers and cardiac tissue.

Content of lectures:

·         Introduction to modelling

·         Ensuring validity of the model

·         Finite element modelling

·         Compartment modelling

·         Modelling of excitable membranes

Literature
Notes, literature and exercise instruction will be distributed at the course

Prerequisites
None

Evaluation
Evaluation by written report. Passed/fail.

Organiser:          Associate Professor Steffen Frahm e-mail: ksf@hst.aau.dk

Lecturers:           Associate Professor Steffen Frahm, ksf@hst.aau.dk – Associate Professor Lars Pilegaard, lpt@hst.aau.dk – Associate Professor Carsten Dahl Mørch,
                            cdahl@hst.aau.dk – Professor Johannes Struijk, jjs@hst.aau.dk and invited lectures

ECTS:                   2.0                                                                                           

Dates:                  2 and 9 October 2023 (08:15-16:15)

Place:                   Aalborg University

Deadline:            11 September 2023

Program:             BEN

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.