The Center for Health Data Science at the Faculty of Health and Medical Sciences, University of Copenhagen, is offering a PhD scholarship in deep learning for gene expression data. Starting date is expected to be Oct 1, 2020.
Center for Health Science Data
The Center for Health Data Science (HeaDS) is a newly formed center at the Faculty of Health and Medical Sciences, which is a hub for data science research at the Faculty and offers support to other research groups. Around 20 top researchers/research groups are members of the Center and we aim to establish more groups within the Center and create a world-class research environment for health data science with close links to the many experimental and clinical groups at the Faculty. HeaDS is located at the Panum Institute. The project will be in the group of head of center, professor Anders Krogh.
Job/Study Description
The expression of all genes in a sample can be measured by RNA-seq and can give a (noisy) high-dimensional snapshot of expression in a sample, for instance a tumor biopsy. In many studies, only few samples are available for each condition, limiting the analyses to single gene comparisons of disease vs normal. In this project, we will use the vast amounts of available RNA-seq data to learn low-dimensional representations of data that can be used to improve analyses in such studies. We will use deep learning, e.g. auto-encoders, and experiment with various ways to include prior information, such as cellular pathways, in the neural network. The methods will be tested on and applied to data sets for specific diseases in collaboration with clinical groups at the Faculty and the University Hospital with the aim to improve diagnosis and treatment.
Required qualifications:
- A master degree in Computer Science, Bioinformatics, Mathematics/Statistics, Physics, Engineering or similar
- Programming experience in Python
- Excellent command of English
- Either experience with gene expression analysis or with deep learning (e.g. Pytorch)
It is expected that applicants have a strong interest in medical applications of data science. Experience in bioinformatics in general, a good understanding of math, and familiarity with R will be considered advantageous.
Supervision
The research will be performed under the supervision of Professor Anders Krogh.
Application Procedure:
Apply by clicking “Apply online” below. Please note that only online applications will be accepted.
Applications – in English – must include:
- Cover Letter detailing your motivation and background for applying. Make sure to include a description for why this particular PhD project is interesting for you.
- CV
- Diploma and transcripts of records (including grades)
- Other information for consideration, e.g. list of publications and/or manuscripts (if any), peer reviewed and others
- Possible references (with contact details – email and telephone numbers) and minimum two letters of recommendation.
The closing date for applications is 23.59 pm, August 5, 2020. Applications received later than this date will not be considered.
Application procedure
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Appointments Committee. All applicants are then immediately notified whether their application has been passed for assessment. An expert assessment committee is appointed in order to make an assessment of the selected applicants for the specific post. Selected applicants are notified of the composition of the committee and each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself. You can read about the recruitment process at jobportal.ku.dk.
Please note that the applicant will be contacted if the assessment committee requires further documentation.
The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities
Read about the recruitment process.
The main criteria for selection will be the candidate’s research potential and the above-mentioned skills. The successful candidate will be requested to formally apply for enrolment as a PhD student at the SUND Graduate School. Employment as a PhD fellow will be conditional on successful enrolment in the PhD programme.
Terms of employment:
The position is offered for a period of three years and employment is governed by the Protocol on PhD Research Fellows signed by the Danish Ministry of Finance and AC (the Danish Confederation of Professional Associations).
Questions:
For specific information about the position, please contact Professor Anders Krogh, anders.krogh@sund.ku.dk. Any questions regarding the application process or administrative queries of any kind should be directed to HR Partner Ditte Maria Bohn, dmbohn@sund.ku.dk.
For more information on working and living in Denmark: http://ism.ku.dk/, and www.workingconditions.ku.dk
The Faculty of Health and Medical Sciences comprises approximately 7500 students, 1500 PhD students and 3200 employees. The Faculty advances the field of health sciences through its core activities: research, teaching, knowledge sharing and communication. With basic research fields ranging from molecular studies to studies of society, the Faculty contributes to a healthy future through its graduates, research findings and inventions benefitting patients and the community. The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.
Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.