Postdoc and/or Assistant Professor in Responsible Machine Learning
We are looking for highly motivated and dynamic young researchers for the position of a Postdoc or Assistant Professor for a period of two years, who can conduct high quality research on topics within responsible Machine. We expect the assistant professor position to start 1 October 2025 or as soon as possible thereafter. The postdoc position is extected to start early 2026.
The candidate will primarily be a member of the research group Foundations of Responsible Machine Learning, led by Amartya Sanyal in the Department of Computer Science, as well as the broader DeLTA lab in the Machine Learning Section.
Our Research Our research focuses broadly on theoretical and applied topics within privacy and robustness of machine learning algorithms.
Your job The hired candidate is expected to both lead independent research within topics of responsible machine learning as well as collaborate with other members of the research group. In addition, the candidate is also expected to regularly publish in top tier conferences in their domain including but not limited to NeurIPS, ICML, ICLR, COLT, ALT, FORC, STOC, FOCS, AISTATS, etc.
The assistant professor’s responsibilities will primarily consist of:
- research, including publication/academic dissemination duties at top tier conferences listed above
- research-based teaching
- sharing knowledge with society
- participation in formal pedagogical training programme for assistant professors
Profile
Six overall criteria apply for assistant professor appointments at the University of Copenhagen. The six criteria (research, teaching, societal impact, organisational contribution, external funding, and leadership) are considered a framework for the overall assessment of candidates. Find information about each criterion here: https://employment.ku.dk/faculty/criteria-for-recognising-merit.
Furthermore, we are looking for a highly motivated and enthusiastic scientist with the following skills and experience:
Essential experience and skills for Postdoc:
- You have a PhD in Computer Science, mathematics, or statistics
- You are highly experienced in theoretical topics within machine learning
- You have an active interest in topics within responsible machine learning
- Proficient communication skills and ability to work in teams
- Excellent English skills written and spoken
Essential experience and skills for Asistant Professor:
- In addition to those mentioned above for postdoc, teaching experience within Computer Science
The decision between Postdoc and Assistant Professor position will be made depending on experience and scientific results after completion of PhD.
Place of employment
The place of employment is at the Department of Computer Science, University of Copenhagen. We offer creative and stimulating working conditions in dynamic and international research environment.
Terms of employment
The average weekly working hours are 37 hours per week.
The position is a fixed-term position limited to a period of 2 years. Extension may be possible closer to the end date after discussion.
Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 38,700 DKK/approx. 5,100 EUR (April 2025 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18,07 % to your pension fund.
Foreign and Danish applicants may be eligible for tax reductions if they hold a PhD degree and have not lived in Denmark the last 10 years.
The position is covered by the Job Structure for Academic Staff at Universities 2025.
Questions
For further information please contact Amartya Sanyal (amsa@di.ku.dk)
Foreign applicants may find this link useful: www.ism.ku.dk (International Staff Mobility).
Application procedure
Your application must be submitted in English by clicking ‘Apply now’ below. Furthermore, your application must include the following documents/attachments – all in PDF format:
- Motivated letter of application (Max. one page)
- CV incl. education, work/research experience, language skills and other skills relevant for the position
- A certified/signed copy of a) PhD certificate and b) Master of Science certificate. If the PhD is not completed, a written statement from the supervisor will do
- List of publications
- Teaching portfolio (If applicable)
Deadline for applications: June 24, 23.59pm CET
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 the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed 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 https://employment.ku.dk/faculty/recruitment-process/
The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.
Interviews are expected to be held in August-September, 2025.
The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.
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.