Welcome to A Cross and inter-disciplinary approach to System thinking – theories and methodologies
Description: ‘As our world continues to change rapidly and become more complex, systems thinking will help us manage, adapt, and see the wide range of choices we have before us. It is a way of thinking that gives us the freedom to identify root causes of problems and see new opportunities’ (Meadows, 2008, p. 1).
With current sustainability problems, human society as we know it, is living on “borrowed time”. And this is shaping how we see and act in the world. As researchers we are called to address complex problems, with societal impact, and to collaborate across disciplines to provide the best possible solution. For example, European Commission calls on missions to drive research and innovation, which AAU already adopted, emphasising cross-disciplinary, cross-institutions collaboration and engaging with multiple stakeholders. Thinking and working through systems should not be taken for granted. Even though history presents “natural” systems thinkers like Einstein, or Gregory Batson, thinking in systems requires a combination of attributes which go beyond the disciplinary knowledge and expertise such as flexibility, openness, collaboration, whilst uncovering the structures and behaviours that describe a given phenomenon and are in root of complex problems. This course aims to support PhD students to conceptualize systems thinking from multiple lenses whilst positioning themselves and their research from a systems perspective.
Prerequisites: No, as long as students are interested in the topic.
Learning objectives:
The course intends to facilitate learning opportunities for PhD students to:
1) participate in conceptual thinking of system thinking as a concept from multiple lenses, from transdisciplinary to multidisciplinary and cross-disciplinary.,
2) collaboratively work on interdisciplinary research designs surrounding the topic of system thinking in diverse scientific fields,
3) develop open-mindedness and wills to work (?) with alternative perspectives to better understand the complexity of reality to address its challenges and problems.
Intended learning outcomes:
Participants are expected to:
1) reflectively conceptualize systems thinking from multiple lenses and its relevance for their current and future research practice,
2) collaboratively propose cross and interdisciplinary research designs to address the complexity of reality in a chosen topic, empowered by the concept of system thinking,
3) critically self and peer evaluate the research designs and propose alternatives to further enhance peer learning in a cross and inter-disciplinary way.
Assessment:
Work on a collaboratively written cross or inter-disciplinary research proposal (3-4 pages) after Day 1 and 2 of the course, provide peer evaluation before Day 3 of the course. Resubmission 2 weeks after Day 3 after collecting all feedback during Day 3. The design shall illustrate the use of one or more theoretical lens of system thinking and methodological design addressing the value and benefits of cross or inter-disciplinary research collaboration.
Course activities:
A problem and project-based learning approach is adopted in this course, involving participants working in group on real-life issues identified on their own.
Organizer: Lykke Bertel, Søren Lykke, and Xiangyun Du
Lecturers: Aida Guerra, Helle Nielsen, Lykke Bertel, Søren Lykke, Thomas Elliot and Xiangyun Du
ECTS: 3
Time: 3 - 5 December 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 12 November 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: ‘As our world continues to change rapidly and become more complex, systems thinking will help us manage, adapt, and see the wide range of choices we have before us. It is a way of thinking that gives us the freedom to identify root causes of problems and see new opportunities’ (Meadows, 2008, p. 1).
With current sustainability problems, human society as we know it, is living on “borrowed time”. And this is shaping how we see and act in the world. As researchers we are called to address complex problems, with societal impact, and to collaborate across disciplines to provide the best possible solution. For example, European Commission calls on missions to drive research and innovation, which AAU already adopted, emphasising cross-disciplinary, cross-institutions collaboration and engaging with multiple stakeholders. Thinking and working through systems should not be taken for granted. Even though history presents “natural” systems thinkers like Einstein, or Gregory Batson, thinking in systems requires a combination of attributes which go beyond the disciplinary knowledge and expertise such as flexibility, openness, collaboration, whilst uncovering the structures and behaviours that describe a given phenomenon and are in root of complex problems. This course aims to support PhD students to conceptualize systems thinking from multiple lenses whilst positioning themselves and their research from a systems perspective.
Prerequisites: No, as long as students are interested in the topic.
Learning objectives:
The course intends to facilitate learning opportunities for PhD students to:
1) participate in conceptual thinking of system thinking as a concept from multiple lenses, from transdisciplinary to multidisciplinary and cross-disciplinary.,
2) collaboratively work on interdisciplinary research designs surrounding the topic of system thinking in diverse scientific fields,
3) develop open-mindedness and wills to work (?) with alternative perspectives to better understand the complexity of reality to address its challenges and problems.
Intended learning outcomes:
Participants are expected to:
1) reflectively conceptualize systems thinking from multiple lenses and its relevance for their current and future research practice,
2) collaboratively propose cross and interdisciplinary research designs to address the complexity of reality in a chosen topic, empowered by the concept of system thinking,
3) critically self and peer evaluate the research designs and propose alternatives to further enhance peer learning in a cross and inter-disciplinary way.
Assessment:
Work on a collaboratively written cross or inter-disciplinary research proposal (3-4 pages) after Day 1 and 2 of the course, provide peer evaluation before Day 3 of the course. Resubmission 2 weeks after Day 3 after collecting all feedback during Day 3. The design shall illustrate the use of one or more theoretical lens of system thinking and methodological design addressing the value and benefits of cross or inter-disciplinary research collaboration.
Course activities:
A problem and project-based learning approach is adopted in this course, involving participants working in group on real-life issues identified on their own.
Organizer: Lykke Bertel, Søren Lykke, and Xiangyun Du
Lecturers: Aida Guerra, Helle Nielsen, Lykke Bertel, Søren Lykke, Thomas Elliot and Xiangyun Du
ECTS: 3
Time: 3 - 5 December 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 12 November 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Lykke Brogaard Bertel
- Teacher: Xiangyun Du
- Teacher: Thomas Elliot
- Teacher: Aida Olivia Pereira de Carvalho Guerra
Welcome to Advanced PhD course on Philosophy of Technology: Relating Technology to Ethics, Politics, and the Empirical through the Lenses of Postphenomenology and Critical Theory of Technology/Critical Constructivism (2025)
Description: During this course a secetion of existing literature on two central positions in philosophy of technology -- postphenomenology and critical theory / critical constructivism -- will be discussed and scutinized. Focus will be on how technologies inform our interpretation of the world, how technology nudge humans to do certain things, how technology is value-ladden and embedded in power structures and normative regimes, and how technologies might exclude vulnerable groups and individuals. Course literature will include a double special issue of Techné entitled "Critical Constructivism and Postphenomenology: Ethics, Politics, and the Empirical" (vol 24, issue 1/2) plus selected case studies applying one of these two positions in an analysis of a technology. Everyone who studies technology, technological implementation and technological innovation in a socio-technical perspective will benefit from the course's thorough discussions and comparison of these two central positions in philosophy of technology, and is a must for ph.d. scholars who in their research touch upon how technologies inform our interpretation of the world, how technology nudge humans to do certain things, how technology is value-ladden and embedded in power structures and normative regimes, how technology excludes vulnerable groups and individuals.
Prerequisites: The course is aimed towards ph.d. scholars working with technology in a socio-technical prespective. Disciplinary diversity is appreciate. Thus, no other disciplinary prerequisites will be enforced.
Learning objectives:
- Knowledge about different philosophy of technology positions and their take on ethics, politics, sensemaking, and empirical work.
- Skills in choosing and linking philosophy of technology frameworks in / to own research.
- Competences in communicating philosophy of technology topics in an interdisciplinary environment.
Organizer: Tom Børsen
Lecturers: Tom Børsen and Lars Botin
ECTS: 2.0
Time: 11 and 12 December 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 15
Deadline: 20 November 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: During this course a secetion of existing literature on two central positions in philosophy of technology -- postphenomenology and critical theory / critical constructivism -- will be discussed and scutinized. Focus will be on how technologies inform our interpretation of the world, how technology nudge humans to do certain things, how technology is value-ladden and embedded in power structures and normative regimes, and how technologies might exclude vulnerable groups and individuals. Course literature will include a double special issue of Techné entitled "Critical Constructivism and Postphenomenology: Ethics, Politics, and the Empirical" (vol 24, issue 1/2) plus selected case studies applying one of these two positions in an analysis of a technology. Everyone who studies technology, technological implementation and technological innovation in a socio-technical perspective will benefit from the course's thorough discussions and comparison of these two central positions in philosophy of technology, and is a must for ph.d. scholars who in their research touch upon how technologies inform our interpretation of the world, how technology nudge humans to do certain things, how technology is value-ladden and embedded in power structures and normative regimes, how technology excludes vulnerable groups and individuals.
Prerequisites: The course is aimed towards ph.d. scholars working with technology in a socio-technical prespective. Disciplinary diversity is appreciate. Thus, no other disciplinary prerequisites will be enforced.
Learning objectives:
- Knowledge about different philosophy of technology positions and their take on ethics, politics, sensemaking, and empirical work.
- Skills in choosing and linking philosophy of technology frameworks in / to own research.
- Competences in communicating philosophy of technology topics in an interdisciplinary environment.
Organizer: Tom Børsen
Lecturers: Tom Børsen and Lars Botin
ECTS: 2.0
Time: 11 and 12 December 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 15
Deadline: 20 November 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Lars Botin
- Teacher: Tom Holmgaard Børsen
Welcome to Advanced Energy System Analysis on the EnergyPLAN model
Description: The PhD course gives an introduction to advanced energy system analysis using the EnergyPLAN computer model. After the course the participants are expected to be able to understand methodologies of advanced energy system analysis and to be able to use the EnergyPLAN computer model as a tool in making energy system analyses.
The course is conducted as a combination of lectures and computer workshops of a total of 4 days (32 hours) and assignments of a total of 6-7 days (52 hours). Results of assignments will be presented by the participants.
The course start with an introduction to the model (installation, using, constructing new data sets) and proceeds to focus on the use of the model in:
- sustainable cities and communities
- technical analyses of large-scale integration of wind.
- analyses of exchange with external electricity markets
- combinations of different renewable energy technologies.
- designing flexible energy systems using flexible technologies such as heat pumps, hydrogen storage, pumped storage etc.
- district heating systems versus individual houses and zero energy buildings
- designing energy systems based on multiple criteria
Prerequisites: Prior to the course all participants are requested to conduct the following:
1. Install EnergyPLAN from energyplan.eu.
2. Consider how you wish to use EnergyPLAN – preferably in your Ph.D. project – alternatively in independent analyses only made for the Ph.D. course (notice that agenda for the first morning – third bullet-point).
3. Read the FIDE guide (Finding and inputting data to EnergyPLAN) from energyplan.eu and consider what data you will need to do).
4. There are a number of training exercises at energyplan.eu You are strongly encouraged /
expected to do these beforehand as this will enable you to make more advanced independent analyses during the actual course.
5. Read the articles.
Learning objectives: The PhD course gives an introduction to advanced energy system analysis using the EnergyPLAN computer model. After the course the participants are expected to be able to understand methodologies of advanced energy system analysis and to be able to use the EnergyPLAN computer model as a tool in making energy system analyses.
Organizer: Henrik Lund
Lecturers: Poul Alberg Østergaard, Henrik Lund, Jakob Zinck Thellufsen and Brian Vad Mathiesen
ECTS: 5
Time: 28 April – 1 Maj 2025 (onsite Aalborg), 6 and 13 May (Q&A online) and 20 May (Exam online)
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 7 April 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: The PhD course gives an introduction to advanced energy system analysis using the EnergyPLAN computer model. After the course the participants are expected to be able to understand methodologies of advanced energy system analysis and to be able to use the EnergyPLAN computer model as a tool in making energy system analyses.
The course is conducted as a combination of lectures and computer workshops of a total of 4 days (32 hours) and assignments of a total of 6-7 days (52 hours). Results of assignments will be presented by the participants.
The course start with an introduction to the model (installation, using, constructing new data sets) and proceeds to focus on the use of the model in:
- sustainable cities and communities
- technical analyses of large-scale integration of wind.
- analyses of exchange with external electricity markets
- combinations of different renewable energy technologies.
- designing flexible energy systems using flexible technologies such as heat pumps, hydrogen storage, pumped storage etc.
- district heating systems versus individual houses and zero energy buildings
- designing energy systems based on multiple criteria
Prerequisites: Prior to the course all participants are requested to conduct the following:
1. Install EnergyPLAN from energyplan.eu.
2. Consider how you wish to use EnergyPLAN – preferably in your Ph.D. project – alternatively in independent analyses only made for the Ph.D. course (notice that agenda for the first morning – third bullet-point).
3. Read the FIDE guide (Finding and inputting data to EnergyPLAN) from energyplan.eu and consider what data you will need to do).
4. There are a number of training exercises at energyplan.eu You are strongly encouraged /
expected to do these beforehand as this will enable you to make more advanced independent analyses during the actual course.
5. Read the articles.
Learning objectives: The PhD course gives an introduction to advanced energy system analysis using the EnergyPLAN computer model. After the course the participants are expected to be able to understand methodologies of advanced energy system analysis and to be able to use the EnergyPLAN computer model as a tool in making energy system analyses.
Organizer: Henrik Lund
Lecturers: Poul Alberg Østergaard, Henrik Lund, Jakob Zinck Thellufsen and Brian Vad Mathiesen
ECTS: 5
Time: 28 April – 1 Maj 2025 (onsite Aalborg), 6 and 13 May (Q&A online) and 20 May (Exam online)
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 7 April 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Henrik Lund
- Teacher: Brian Vad Mathiesen
- Teacher: Jakob Zinck Thellufsen
- Teacher: Poul Alberg Østergaard
Welcome to Python Programming for Geospatial Analysis
Description: The PhD course Python for Geospatial Analysis will provide an introduction to Python with a focus on mapping, exploring, processing, and analysing geospatial information using Python. Participants will learn how tasks traditionally conducted in a desktop GIS system can be easily transferred to Python code and therefore made faster, more flexible, and completely reproducible, which is an aspect of increasing importance in many research fields. At the end of this course, participants will have a solid understanding of the capabilities of core Python modules for geospatial information such as fiona, geopandas, pysal, or rasterio and be able to apply them in their own research. This course will focus on geospatial analysis in “pure” Python, i.e., automation of tasks in ArcGIS or QGIS with Python is out of scope for this course. However, participants looking to do this should be sufficiently proficient in Python after this course to accomplish these tasks on their own.
Day 1: General introduction to Python, mapping and explorative analysis of geographic information
Day 2: The Python stack for geospatial analysis
Day 3: Using geospatial web services from Python
Prerequisites: The course will introduce Python from scratch (i.e., no previous experience in Python is required), however participants should have a basic understanding of programming principles, e.g. know what a variable, a function, or a loop is. Likewise, we do not expect participants to be GIS experts, but again, a basic understanding of geographic information concepts such as layers or vector/raster formats. Ideally, participants in this course would already be using GIS in some way for their research and be looking for ways to do this more efficiently.
Learning objectives: The participants will be able to use python for - automating generic tasks such as e.g., downloading online data and basic data science tasks, - interacting with cloud services and processing data in the cloud systems, - visualising, processing, and analysing geospatial data using geospatial methods, - solving their own self-defined tasks related to their PhD.
Organizer: Jamal Jokar Arsanjani
Lecturers: Jamal Jokar Arsanjani, Carsten Kessler, Ida Maria Bonnevie, Irma Kveladze
ECTS: 3
Time: 14 - 16 May 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 20
Deadline: 23 April 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: The PhD course Python for Geospatial Analysis will provide an introduction to Python with a focus on mapping, exploring, processing, and analysing geospatial information using Python. Participants will learn how tasks traditionally conducted in a desktop GIS system can be easily transferred to Python code and therefore made faster, more flexible, and completely reproducible, which is an aspect of increasing importance in many research fields. At the end of this course, participants will have a solid understanding of the capabilities of core Python modules for geospatial information such as fiona, geopandas, pysal, or rasterio and be able to apply them in their own research. This course will focus on geospatial analysis in “pure” Python, i.e., automation of tasks in ArcGIS or QGIS with Python is out of scope for this course. However, participants looking to do this should be sufficiently proficient in Python after this course to accomplish these tasks on their own.
Day 1: General introduction to Python, mapping and explorative analysis of geographic information
Day 2: The Python stack for geospatial analysis
Day 3: Using geospatial web services from Python
Prerequisites: The course will introduce Python from scratch (i.e., no previous experience in Python is required), however participants should have a basic understanding of programming principles, e.g. know what a variable, a function, or a loop is. Likewise, we do not expect participants to be GIS experts, but again, a basic understanding of geographic information concepts such as layers or vector/raster formats. Ideally, participants in this course would already be using GIS in some way for their research and be looking for ways to do this more efficiently.
Learning objectives: The participants will be able to use python for - automating generic tasks such as e.g., downloading online data and basic data science tasks, - interacting with cloud services and processing data in the cloud systems, - visualising, processing, and analysing geospatial data using geospatial methods, - solving their own self-defined tasks related to their PhD.
Organizer: Jamal Jokar Arsanjani
Lecturers: Jamal Jokar Arsanjani, Carsten Kessler, Ida Maria Bonnevie, Irma Kveladze
ECTS: 3
Time: 14 - 16 May 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 20
Deadline: 23 April 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Ida Maria Bonnevie
- Teacher: Jamal Jokar Arsanjani
- Teacher: Carsten Keßler
- Teacher: Irma Kveladze
Welcome to Public Speaking and Oral Communication
Description:
Do you get nervous presenting in front of a group or wish to improve your public speaking skills? This course is for you! Whether defending a thesis, delivering conference talks, or attending job interviews, effective communication is crucial for PhD students.
This course is designed to enhance your public speaking and oral communication skills in face-to-face contexts. Emphasis will be placed on the fundamental and technical aspects of oral communication, such as pitch, cadence, projection, and presence. Students will engage in self-reflection and receive feedback from both the instructor and peers, helping them identify their strengths and address their weaknesses.
The course is divided into two parts:
Fundamentals: Covering theories and principles of public speaking and oral communication.
Practice: Involving in-person exercises (e.g. small group work), speech writing/preparation, giving a short speech, and constructive feedback.
Prior to the in-person portion of the class (21-23 May), students will start with online materials (on-demand, e.g. videos and articles) to help lay a foundation of principles of public speaking. In-class time will be focused on overview and implementation of principles via exercises and feedback, culminating in a short speech given in front of the class.
Learning objectives:
This course aims to equip students with the necessary knowledge and skills for effective oral communication involving articulating their ideas, engaging listeners, and communicating with clarity. By the end of this course, students will feel comfortable giving a talk in front of an audience in a compelling and clear manner and present themselves with confidence.
Organizer: Furqan Asif
Lecturers: Furqan Asif
ECTS: 3
Time: 21 - 23 May 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 30 April 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description:
Do you get nervous presenting in front of a group or wish to improve your public speaking skills? This course is for you! Whether defending a thesis, delivering conference talks, or attending job interviews, effective communication is crucial for PhD students.
This course is designed to enhance your public speaking and oral communication skills in face-to-face contexts. Emphasis will be placed on the fundamental and technical aspects of oral communication, such as pitch, cadence, projection, and presence. Students will engage in self-reflection and receive feedback from both the instructor and peers, helping them identify their strengths and address their weaknesses.
The course is divided into two parts:
Fundamentals: Covering theories and principles of public speaking and oral communication.
Practice: Involving in-person exercises (e.g. small group work), speech writing/preparation, giving a short speech, and constructive feedback.
Prior to the in-person portion of the class (21-23 May), students will start with online materials (on-demand, e.g. videos and articles) to help lay a foundation of principles of public speaking. In-class time will be focused on overview and implementation of principles via exercises and feedback, culminating in a short speech given in front of the class.
Learning objectives:
This course aims to equip students with the necessary knowledge and skills for effective oral communication involving articulating their ideas, engaging listeners, and communicating with clarity. By the end of this course, students will feel comfortable giving a talk in front of an audience in a compelling and clear manner and present themselves with confidence.
Organizer: Furqan Asif
Lecturers: Furqan Asif
ECTS: 3
Time: 21 - 23 May 2025
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 30 April 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Furqan Asif
Welcome to Advanced LCA – Consequential and IO-based Life Cycle Assessment (2025)
Description:
The course aims at strengthening skills in life cycle inventory analysis. The course targets the development of advanced competences in LCA by applying the problem based-learning (PBL) teaching model that focuses on learning by doing and reflection. We also apply a hybrid (online + physical) and flipped classroom approach where materials (readings, videos) are provided to the students in advance and the time spent in classroom/videomeeting is used for Q&A, hands-on exercises, discussions. The course activities will include intensive group work, problem defining and solving applied to real-word cases, practical exercises, and discussion sessions or workshops. The target audience of the course is academics (PhDs, postdoc, other) or professionals who already have basic experience with LCA and intend to bring their LCA competences to an advanced level. Basic experience means for example having carried out simple LCAs before or having elementary knowledge of LCA theory. The course content is organized in three modules.
Module 1. Consequential LCA
Students will learn the fundamentals of Consequential LCA. Topics covered: Introduction to attributional and consequential models. Algorithms for performing consequential LCA in the definition of functional unit, consumption mix, and identification of determining and dependent coproducts. Communicating consequential models. The module includes exercises.
Module 2. Stochastic LCA
In this hands-on module students will learn how to use the software Brightway2 for stochastic and other LCA simulations. Topics covered: Computational structure of LCA. Computer simulation and statistical approaches for uncertainty and sensitivity analysis in LCA. LCA reproducibility and data sharing. The module includes exercises.
Module 3. Input output LCA
Students will learn the fundamentals of Input-Output modelling. Topics covered: supply-use tables, multi-regional models and trade linking. Integrating process LCA and IO-analysis via hybrid LCA, tiered and embedded. The module includes exercises.
Prices
Attendee / Price*
PhD students affiliated to a Danish University / Free
PhD students not affiliated to a Danish University / 4.500 DKK (600 EUR)
Academics (e.g. postdoc and professors) / 9.000 DKK (1200 EUR)
Professionals (consultancy, industry, etc.) / 18.000 DKK (2400 EUR)
* Prices do not cover meals or accommodation
Organizers: The course is organized by The Technical Doctoral School of IT and Design, Aalborg University and Danish Centre for Environmental Assessment (DCEA) www.DCEA.dk, in collaboration with the International Life Cycle Academy (ILCA) www.ILCA.es
Registration and info: Please apply via mail to the course organizer Massimo Pizzol (massimo@plan.aau.dk). You must provide the following information in the email: Full name / Profession (PhD student, postdoc, consultant…) / Institution name / Address / email address / Phone nr / your research field or Phd topic / your experience with LCA
ECTS: 5.0
*One ECTS credit is equivalent to 28 hours of work
Activities: Includes attending to the lectures and performing exercises in class.
Readings: Approx. 100 pages of scientific articles and reports, that are provided to the students, plus python tutorials and videos.
Group work: students work in groups (max 5 people). Each group will work on a case study and apply the knowledge of the course on the case study.
EXAMPLE, a group works on an LCA of a product and does:
- prior to the course: choice of product and data mining, getting base knowledge and data to describe the product system.
- during the course (exercises in class): consequential inventory with matrix format, IO LCA inventory, inclusion of iLUC, inclusion of social impacts, etc.
- after the course: organize the material and prepare a portfolio/article where all the techniques are presented for the case study.
Eventually, all portfolios are made available. Each student will thus get the info on five different cases. Students should be able to organize themselves using online tools (skype, dropbox etc) to collaborate in group remotely prior and after the course.
Prerequisites: The course requires basic knowledge of Life Cycle Assessment, i.e. the knowledge of the tool that one might get at bachelor or master level. This means that the students need to have either a strong theoretical understanding of LCA or practical experience (having done some LCA studies before, even if simple). We don't teach the basics, and select the students based on their prior experience to make an homogeneous group and ensure a high starting level. In this way we can teach more advanced topics that are fit for a PhD level course.
Learning Objectives:
- Knowledge
- Theoretical elements cover: computational structure of LCA, computer simulation, uncertainty and sensitivity analysis in LCA context, system models in LCA, algorithms for consequential LCA, monetary supply and use tables and different models for creating IO-model and hybrid LCA.
- Skills
- Practical modelling skills with software Brightway2, including uncertainty and sensitivity analysis (local and global). Practical skills in consequential LCA modelling including identification of functional unit, consumption mix, and solving multifunctionality via substitution.
- Communicating consequential LCA models. Modelling indirect land use changes in LCA. Practical skills in using IO and hybrid LCA.
- Competences
- Apply advanced software, modelling approaches, and databases to address, solve, and communicate complex prospective questions on the life-cycle impact of products, within a research context and beyond.
Organizer: Massimo Pizzol (Prof.)
Lecturers:
Massimo Pizzol, Professor
Jannick Schmidt, Professor
Søren Løkke, Associate professor
Agneta Ghose, Postdoc
Time:
Online (all times 10:00-12:00)
Week 13 - Tue 25 March 2025
Week 13 - Thu 27 March 2025
Week 15 - Tue 8 April 2025
Week 15 - Thu 10 April 2025
Week 17 - Tue 22 April 2025
Week 17 - Thu 24 April 2025
Onsite (all days 08:00-16:00)
Week 20 - 12, 13, 14 May 2025, Monday to Wednesday
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 4 March 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description:
The course aims at strengthening skills in life cycle inventory analysis. The course targets the development of advanced competences in LCA by applying the problem based-learning (PBL) teaching model that focuses on learning by doing and reflection. We also apply a hybrid (online + physical) and flipped classroom approach where materials (readings, videos) are provided to the students in advance and the time spent in classroom/videomeeting is used for Q&A, hands-on exercises, discussions. The course activities will include intensive group work, problem defining and solving applied to real-word cases, practical exercises, and discussion sessions or workshops. The target audience of the course is academics (PhDs, postdoc, other) or professionals who already have basic experience with LCA and intend to bring their LCA competences to an advanced level. Basic experience means for example having carried out simple LCAs before or having elementary knowledge of LCA theory. The course content is organized in three modules.
Module 1. Consequential LCA
Students will learn the fundamentals of Consequential LCA. Topics covered: Introduction to attributional and consequential models. Algorithms for performing consequential LCA in the definition of functional unit, consumption mix, and identification of determining and dependent coproducts. Communicating consequential models. The module includes exercises.
Module 2. Stochastic LCA
In this hands-on module students will learn how to use the software Brightway2 for stochastic and other LCA simulations. Topics covered: Computational structure of LCA. Computer simulation and statistical approaches for uncertainty and sensitivity analysis in LCA. LCA reproducibility and data sharing. The module includes exercises.
Module 3. Input output LCA
Students will learn the fundamentals of Input-Output modelling. Topics covered: supply-use tables, multi-regional models and trade linking. Integrating process LCA and IO-analysis via hybrid LCA, tiered and embedded. The module includes exercises.
Prices
Attendee / Price*
PhD students affiliated to a Danish University / Free
PhD students not affiliated to a Danish University / 4.500 DKK (600 EUR)
Academics (e.g. postdoc and professors) / 9.000 DKK (1200 EUR)
Professionals (consultancy, industry, etc.) / 18.000 DKK (2400 EUR)
* Prices do not cover meals or accommodation
Organizers: The course is organized by The Technical Doctoral School of IT and Design, Aalborg University and Danish Centre for Environmental Assessment (DCEA) www.DCEA.dk, in collaboration with the International Life Cycle Academy (ILCA) www.ILCA.es
Registration and info: Please apply via mail to the course organizer Massimo Pizzol (massimo@plan.aau.dk). You must provide the following information in the email: Full name / Profession (PhD student, postdoc, consultant…) / Institution name / Address / email address / Phone nr / your research field or Phd topic / your experience with LCA
ECTS: 5.0
*One ECTS credit is equivalent to 28 hours of work
Activities: Includes attending to the lectures and performing exercises in class.
Readings: Approx. 100 pages of scientific articles and reports, that are provided to the students, plus python tutorials and videos.
Group work: students work in groups (max 5 people). Each group will work on a case study and apply the knowledge of the course on the case study.
EXAMPLE, a group works on an LCA of a product and does:
- prior to the course: choice of product and data mining, getting base knowledge and data to describe the product system.
- during the course (exercises in class): consequential inventory with matrix format, IO LCA inventory, inclusion of iLUC, inclusion of social impacts, etc.
- after the course: organize the material and prepare a portfolio/article where all the techniques are presented for the case study.
Eventually, all portfolios are made available. Each student will thus get the info on five different cases. Students should be able to organize themselves using online tools (skype, dropbox etc) to collaborate in group remotely prior and after the course.
Prerequisites: The course requires basic knowledge of Life Cycle Assessment, i.e. the knowledge of the tool that one might get at bachelor or master level. This means that the students need to have either a strong theoretical understanding of LCA or practical experience (having done some LCA studies before, even if simple). We don't teach the basics, and select the students based on their prior experience to make an homogeneous group and ensure a high starting level. In this way we can teach more advanced topics that are fit for a PhD level course.
Learning Objectives:
- Knowledge
- Theoretical elements cover: computational structure of LCA, computer simulation, uncertainty and sensitivity analysis in LCA context, system models in LCA, algorithms for consequential LCA, monetary supply and use tables and different models for creating IO-model and hybrid LCA.
- Skills
- Practical modelling skills with software Brightway2, including uncertainty and sensitivity analysis (local and global). Practical skills in consequential LCA modelling including identification of functional unit, consumption mix, and solving multifunctionality via substitution.
- Communicating consequential LCA models. Modelling indirect land use changes in LCA. Practical skills in using IO and hybrid LCA.
- Competences
- Apply advanced software, modelling approaches, and databases to address, solve, and communicate complex prospective questions on the life-cycle impact of products, within a research context and beyond.
Organizer: Massimo Pizzol (Prof.)
Lecturers:
Massimo Pizzol, Professor
Jannick Schmidt, Professor
Søren Løkke, Associate professor
Agneta Ghose, Postdoc
Time:
Online (all times 10:00-12:00)
Week 13 - Tue 25 March 2025
Week 13 - Thu 27 March 2025
Week 15 - Tue 8 April 2025
Week 15 - Thu 10 April 2025
Week 17 - Tue 22 April 2025
Week 17 - Thu 24 April 2025
Onsite (all days 08:00-16:00)
Week 20 - 12, 13, 14 May 2025, Monday to Wednesday
Place: Aalborg University
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 4 March 2025
Important information concerning PhD courses:
There is 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 the 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 of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Agneta Ghose
- Teacher: Søren Løkke
- Teacher: Massimo Pizzol
- Teacher: Jannick Schmidt