211-0715/25-2E Associate Professor in machine learning for pharmaceutical sciences Part-time

Associate Professor in Machine Learning for Pharmaceutical Sciences

We seek to employ a group leader at the intersection of machine learning (ML) and drug discovery or development. The position is for 4 years, anchored at Department of Computer Science (DIKU) and associated with the Centre for Pharmaceutical Data Science Education (CPDSE). As a starting package, the position includes a fully financed Ph.D. stipend and a two-year postdoc.

The Centre for Pharmaceutical Data Science Education is a joint effort by seven departments at two universities to raise the data literacy of people discovering, developing, and helping with the right usage of drugs. We aim to rapidly evolve pharmaceutical education, provision, and integrate data-heavy and modelling-heavy research and contribute to progressing the cultures and mindsets in people and organisations involved in the pharma value chain. To do this, we are creating and joining expertise at the universities and the broader ecosystem. The Centre aims to be human-centric and characterized by co-leadership and high levels of autonomy and empowerment.

An important role is to bridge research and teaching at the Department of Computer Science (DIKU) and the other partners in CPDSE, and the group leader is expected to spend approximately 50% of their time in the Machine Learning Section at DIKU and 50% at CPDSE across the street.

The group leader should establish a research group with a focus on developing ML techniques relevant to drug discovery or drug development. DIKU has a strong foundation in data science and ML, and several research groups at DIKU and CPDSE already work with ML on molecular, genome, and transcriptome perturbations. The new group leader (and group) should interface with these existing activities, serving as a hub for pharmaceutical ML and ensuring that methodological work is focused on problems with real impact for drug discovery or development. The bridge between departments is also crucial for teaching relevant courses for pharmaceutical data science and for co-supervised MSc and PhD projects.

The candidate is expected to have:

• A PhD in Computer Science, bioinformatics, or a related field
• A solid foundation in machine learning
• Proven experience in ML applications in drug discovery/development or related areas
• Commitment to develop and engage in joint research, teaching, and organizational co-leadership with other staff in CPDSE
• Genuine interest and experience in teaching at university level – education is an important part of our mission.

Applicants are required to have university level teaching experience, documented teaching competencies and must be able to explain and reflect upon own teaching practice and portfolio. Formal pedagogical training or supervision equivalent to the University of Copenhagen teacher training programme for assistant professors is required.

Duties include the applicant's own research, development of the field, assessment tasks, grant applications, and research management such as supervision and training of research fellows and other staff. The successful applicant must also teach, supervise, prepare and participate in examinations, and fulfill other tasks requested by the Department.

Assessment of applicants will primarily consider their level of documented, original scientific production at an international level, including contributions to developments in their field, as well as their documented teaching qualifications. Managerial and out-reach qualifications of applicants including ability to attract external funding will also be considered.

Six overall criteria apply for associate professor appointments at the University of Copenhagen. The six criteria (research, teaching, societal impact, organizational contribution, external funding and leadership) are considered a framework for an overall assessment of the candidates. Furthermore, each candidate must be assessed according to the specific requirements stated in the job advertisement.

The candidate will be formally employed at the Department of Computer Science, in the section for Machine Learning. The section provides a strong, international environment for research within Machine Learning, ranging from learning theory to information retrieval, image analysis and ML4Science. It is housed within the main Science Campus which is located centrally in Copenhagen. Inquiries about the position can be made to head of department Ken Friis Larsen.

The position is open from 1 September 2026 or as soon as possible thereafter.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

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 Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State. Negotiation for salary supplement is possible.

The application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include:

• Curriculum vitae including information about external funding
• Diplomas (Master and PhD degree or equivalent)
• Research plan – description of current and future research plans
• Description and documentation of teaching experience and qualifications
• Complete publication list
• Separate reprints of 5 particularly relevant papers

The deadline for applications is 19 April 2026, 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.

Interviews will be held on 19 June 2026.

Please refer to the following no. in future communication in this case: 211-0715/25-2E.