Biotechnology, Chemistry and Environmental Engineering (2022)

Description:
This PhD course focuses on developing your competences in presenting your research for fellow PhD students within bioscience and chemistry. The course is organized as a series of seminars where students will be presenting their PhD project orally in plenum in a way that makes it relevant and exciting for students that are not necessarily specialists in the field you are specialized in. For each presentation there will be an ‘opponent’ group’ responsible for preparing questions and chairing the sessions. Further, we will have poster sessions where students will be preparing and presenting a poster with feedback from attending PhD students and organizers. Again, focus will be on preparing a poster and a presentation that attempt to make the content understandable and of interest to researchers that are not specialists in your fields but at the same time does not compromise scientific excellency. Further, the course will include lectures by the organizers on carrier planning and input on how to optimize chances to obtain grant money to continue in science after your PhD.      

Prerequisites:
All students enrolled in a PhD program at the faculty of Engineering and Science are welcome but the course is most relevant for students in the fields of bioscience and chemistry.

Learning objectives:
1. Reflect on, and develop, your oral and written presentation skills
2. Understand what makes for a good oral and written presentation to colleagues not specialised in the field 
3. Understand the funding landscape relevant for young researchers and mature your short and long-term carrier plans
4. Develop abilities to chair and facilitate scientific discussions in plenum

Organizers:
Prof. Morten Mattrup Smedskjær (MMS), mos@bio.aau.dk and Prof. Torsten Nygård Kristensen (TNK), tnk@bio.aau.dk. MMS and TNK are both from the Department of Chemistry and Bioscience, AAU 

Lecturers:
Morten Mattrup Smedskjær, Torsten Nygård Kristensen and participating PhD students.

ECTS: 1.5

Time: 2022 (spring and fall semester)

Friday April 29, 10:00-14:00 – FBV 7H, seminar room in level 1

Friday June 3, 10:00-14:00 – FBV 7H, glass room in level 1

Friday September 30, 10:00-14:00 – FBV 7H, glass room in level 1

Friday October 28, 10:00-14:00 – FBV 7H, glass room in level 1

Friday November 25, 10:00-14:00 – FBV 7H, glass room in level 1

-- Lunch will be provided

Number of seats:

Deadline: April 1, 2022

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:
Modern laboratory equipment produces huge amounts of experimental data — spectral vectors with hundreds of wavelengths, microarrays, gene expression data, sensors, multi-channel images and many others. Even conventional measurements may end up with tens to hundreds of variables. Such data represent a wealth of potential information but usually only a part of it relates to a problem of interest.

This course teaches how to extract problem-dependent information from multivariate data. The practical part of the course assuming using R for calculations and visualization of results.

The course is split in to two parts. The first part (3 days, 2 ECTS) introduces descriptive and inferential statistics, as well as data exploration with Principal Component Analysis. The second part (3 days, 2 ECTS) is mainly devoted to supervised analysis of multivariate data, including regression and validation, preprocessing and variable selection as well as classification.

In each part lectures are supplemented with a suite of real life examples and exercises as well as assignments, with which students will try the discussed methods by solving various data analysis problems. To complete the course, participants have to work on three mini-projects and submit their results in form of reports within 1-2 month after the main part if finished.

Organizer: Associate Professor Sergey Kucheryavskiy, E-mail svk@bio.aau.dk

Lecturers: Associate Professor Sergey Kucheryavskiy

ECTS: 4.0

Time: 16-18 November and 21-23 November 2022

Place: Section of Chemical Engineering, Aalborg University, campus Esbjerg, Niels Bohrs vej, 8, DK-6700, Esbjerg, Denmark

Number of seats:

Deadline: 26 October 2022

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.