PhD Fellowships in Machine Learning/Quantum Machine Learning for Health Data Science

University of Copenhagen Department of Computer Science


PhD Fellowships in Machine Learning or Quantum Machine Learning for Health Data Science

Department of Computer Science
Faculty of Science
University of Copenhagen

Two to three Ph.D. fellowships are available in the group of Professor Anders Krogh ( from the 1 December 2022, or as soon as possible after that.

The group focusses on development of deep generative models, quantum machine learning, and applications to medical data. We are seeking people to do research on one or more of these topics:

  1. Quantum machine learning for biological applications. We are seeking people that can develop quantum algorithms for generative neural networks together with our theoretical and experimental collaborators in math and physics.
  2. Development of deep generative neural networks. We are seeking people with a good theoretical background, who can also work on implementations and applications.
  3. Applications of generative models to medical data such as gene expression data and clinical data. Part of this work is in the EU project GenomeMed4ALL.

We seek highly motivated people that can contribute to the theoretical and applied work in the group. The group is part of “Center for Basic Machine Learning Research in Life Science” ( as well as the Center “Quantum for Life” (, and it is expected that you work with other people in the centers. The principal supervisor will be Anders Krogh, but PhD students will generally have a co-supervisor from another group in one of the centers.

Further information on the Department is linked at Inquiries about the positions can be made to Anders Krogh,

Qualifications needed
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) in computer science, physics, mathematics, bioinformatics or closely related field. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.

Additionally, you are expected to

  • Have a good background in machine learning and/or quantum computing
  • Have programming experience (Python)
  • Have a good understanding of math and statistics
  • Be fluent in English
  • Be responsible and self-motivated

Terms of employment
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.

Terms of appointment and payment accord to the agreement between the Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State. The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in the PhD program

  • 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

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) including information about the field of interest (points 1-3 above)
  2. Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position
  3. Original diplomas for 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 relevant)
  5. Reference letters (if available)

Application deadline: The deadline for applications is 3 October 2022, 23:59 GMT +2.

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

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:

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.


Application deadline: 03-10-2022
Employment start: 01-12-2022
Working hours: Full time
Department/Location: Department of Computer Science

In your application, please refer to


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