Hourly paid PhD fellow in machine learning applications for gene expression analysis
Department of computer science
Faculty of Science
University of Copenhagen
Department of Computer Science, Faculty of Science at University of Copenhagen is offering a position as hourly paid PhD fellow in machine learning applications for gene expression analysis commencing 1 August 2021 or as soon as possible thereafter.
Description of the scientific environment
The position is in the group of Professor Anders Krogh. The group works in bioinformatics and machine learning with a focus on algorithms for biological sequence analysis, deep representation learning and gene expression analysis. We are part of the Machine Learning Section, which conducts basic research in machine learning and with applications in many different fields.
In this project, we are applying representation learning to RNA-seq data. The project involves data mangling and preliminary analyses, selection of genes and features for learning, and test of several methods for representation learning.
Principal supervisor is Professor Anders Krogh, Department of Computer Science, email@example.com, 5182 7056.
Your key tasks as a PhD student at SCIENCE are:
- To manage and carry out your research project
- Attend PhD courses
- Write scientific articles and your PhD thesis
- Teach and disseminate your research
- To stay at an external research institution for a few months, preferably abroad
- Work for the department
Applicants should hold an MSc degree in Bioinformatics (or similar) with good results and good English skills. As criteria for the assessment of your qualifications emphasis will also be laid on previous publications (if any) and relevant work experience.
Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.
Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State, appendix 5 C.
The position is available until 31 August 2022 with an average number of working hours of 10 hours per week.
The hourly salary is DKK 219.58 (1 February 2021).
The application, in English, must be submitted electronically by clicking APPLY NOW below.
- Cover Letter,
- Diploma and transcripts of records (BSc and MSc)
- Other information for consideration, e.g. list of publications (if any)
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
The deadline for applications is 14 June 2021, 23:59 GMT +2.
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. Afterwards an assessment committee will be appointed to evaluate the selected applications. The applicants will be notified of the composition of the committee and the final selection of a successful candidate will be made by the Head of Department, based on the recommendations of the assessment committee and the interview committee.
The main criterion for selection will be the research potential of the applicant and the above mentioned skills. The successful candidate will then be requested to formally apply for enrolment as a PhD student at the PhD school of Science. You can read more about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
For specific information about the PhD scholarship, please contact Anders Krogh, Department of Computer Science, firstname.lastname@example.org, 5182 7056.
General information about PhD programmes at SCIENCE is available at https://www.science.ku.dk/phd.
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.