211-1309/22-2H PhD fellowship in Machine Learning for Biology

at University of Copenhagen
Published December 24, 2022
Location Copenhagen, Denmark
Category Machine Learning  
Job Type Scholarship  


The department of Computer Science, Machine Learning section invites applicants for a PhD fellowship in Protein Representation Learning. The project is part of the Center for Basic Machine Learning in Life Science financed by the Novo Nordisk Foundation.

Start date is expected to be 1 April 2023 or as soon as possible thereafter.

The project
We increasingly rely on learned representations to reason about proteins. Large pre-trained language models make it possible to encode raw protein sequences into abstract embeddings, and many classic Bioinformatics tools from the last decades are now being redesigned to work with such embeddings, often resulting in substantial performance gains. Protein structural data has also become much more readily available in the last years, due to advances in protein structure prediction, and embedding models conditioned on protein structure input are now also becoming available.

One issue that is still under-explored is representation learning and generative modelling of protein structure and sequence jointly. In particular for protein engineering, where we wish to understand the structural consequences of amino acid substitutions, this is an important open problem. The goal of the PhD project is to develop new strategies to address this problem. The project will explore techniques to generatively model protein structure, e.g. point-cloud, graph-based, voxel-based representations, and include considerations about rotational invariance/equivariance and other geometric constraints. Particular emphasis will be put on modelling the changes of structural topology induced by mutations (changes in the number of side chain atoms), and the corresponding change of protein structure (thermal fluctuations and larger conformational changes). Finally, the project will explore whether the representations extracted from such generative models can form the basis for more efficient (and interpratable) protein optimization procedures.

Who are we looking for?
The applicant should have a solid background in Machine Learning/Statistics, and is expected to have significant prior experience with programming (preferably Python). Applicants should hold a MSc degree in computer science, bioinformatics, statistics, physics, chemistry or a closely related field, or be in the final stages of acquiring such a degree.  Candidates must have good interpersonal and communication skills. The group is international and fluency in spoken and written English is a requirement. As criteria for the assessment of your qualifications emphasis will also be laid on previous publications (if any) and relevant work experience.

Our group and research- and what do we offer?
The research will be conducted in the BioML group, which works on Machine Learning methods for solving biological problems - with particular focus on generative models for protein sequence and structure. It is headed by Wouter Boomsma and currently holds 6 PhD students and one postdoc, with backgrounds ranging from machine learning/statistics to biochemistry. The group is part of the Machine Learning Section at the Department of Computer Science, which provides a strong, international environment for research within Machine Learning and Information Retrieval, located centrally in Copenhagen. The BioML group is part of the Center for Basic Machine Learning in Life Science, and the PhD student employed by this call would interact regularly with the other PhD students in this Center. For details about the group, see https://ku-bioml.github.io.

Principal supervisor is Professor Wouter Boomsma, Department of Computer Science, wb@di.ku.dk.

The PhD programme
Depending of your level of education, you can undertake the PhD programme as either:

Option A: A three year full-time study within the framework of the regular PhD programme (5+3 scheme), if you already have an education equivalent to a relevant Danish master’s degree.

Option B: An up to five year full-time study programme within the framework of the integrated MSc and PhD programme (the 3+5 scheme), if you do not have an education equivalent to a relevant Danish master´s degree – but you have an education equivalent to a Danish bachelors´s degree.


Option A: Getting into a position on the regular PhD programme

Qualifications needed for the regular programme
To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. computer science. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.

Terms of employment in the regular programme
Employment as PhD fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The terms of employment and salary are in accordance to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Option B: Getting into a position on the integrated MSc and PhD programme

Qualifications needed for the integrated MSc and PhD programme

If you do not have an education equivalent to a relevant Danish master´s degree, you might be qualified for the integrated MSc and PhD programme, if you have an education equivalent to a relevant Danish bachelor´s degree. Here you can find out, if that is relevant for you: General assessments for specific countries and Assessment database.

Terms of the integrated programme
To be eligible for the integrated scholarship, you are (or are eligible to be) enrolled at one of the faculty’s master programmes in computer science.

Students on the integrated programme will enroll as PhD students simultaneously with completing their enrollment in this MSc degree programme.

The duration of the integrated programme is up to five years, and depends on the amount of credits that you have passed on your MSc programme. For further information about the study programme, please see: www.science.ku.dk/phd, “Study Structures”.

Until the MSc degree is obtained, (when exactly two years of the full 3+5 programme remains), the grant will be paid partly in the form of 48 state education grant portions (in Danish: “SU-klip”) plus salary for work (teaching, supervision etc.) totalling a workload of at least 150 working hours per year.
A PhD grant portion is DKK 6,243.

When you have obtained the MSc degree, you will transfer to the salary-earning part of the scholarship for a period of two years. At that point, the terms of employment and payment will be according to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in both PhD programmes

  • Complete and pass the MSc education in accordance with the curriculum of the MSc programme

(ONLY when you are attending the integrated MSc and PhD programme)

  • Carry through an independent research project under supervision
  • Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
  • Participate in active research environments, including a stay at another research institution, preferably abroad
  • Teaching and knowledge dissemination activities
  • Write scientific papers aimed at high-impact journals
  • Write and defend a PhD thesis on the basis of your project


We are looking for the following qualifications:

  • Professional qualifications relevant to the PhD project
  • Relevant publications
  • Relevant work experience
  • Other relevant professional activities
  • Curious mind-set with a strong interest in machine learning
  • Good language skills


Application and Assessment Procedure
Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include:

  1. Motivated letter of application (max. one page)
  2. Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position
  3. Original diplomas for Bachelor of Science or Master of Science and transcript of records in the original language, including an authorized English translation if issued in another language than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted.
  4. Publication list (if possible)
  5. Reference letters

Application deadline:
The deadline for applications is 22 January 2022, 23:59 GMT +1.

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process
After deadline, a number of applicants will be selected for academic assessment by an unbiased expert assessor. You are notified, whether you will be passed for assessment.

The assessor will assess the qualifications and experience of the shortlisted applicants with respect to the above mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.

Interviews with selected candidates are expected to be held mid- February 2023.

For specific information about the PhD fellowship, please contact the principal supervisor.

General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website: https://www.science.ku.dk/phd/.

The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.