Postdoctorate Fellowship in Machine Learning

The Department of Computer Science invites applicants for a 24 month postdoctorate fellowship with a possibility for extension in Multi-Modal Representation Learning for Design of Sustainable Food Processing. The project is part of the larger research project “AI4NaturalFood”, in collaboration with the Department of Food Science, and the project is financed by the Novo Nordisk Foundation.

Start date is 1st October, 2025 or as soon as possible thereafter.

The project

The project is about developing machine learning (ML) methods that help to develop the food of the future. The successful candidate is expected to conduct basic research in ML and to contribute to the application of ML in the food science.

Currently, plant ingredients are often refined to almost molecular purity - and then combined again to create structured foods. This isolation is resource intensive, and the removal of fibre and micronutrients can compromise the nutritional value. This can be mitigated by applying milder forms of processing that do not fully refine ingredients and leave some of the native structure of the plant material intact. These less refined ingredients however exhibit complex behaviour, and we therefore need machine learning to direct the experimental data generation that will be carried out by other team members in the project.

Learning meaningful representation spaces that model the complex space of ingredients and their properties can be immensely useful. These representation spaces can be informed by multiple modalities of data, spanning time-series data, microscopy images, rheological measurements, and so on. Integrating these modalities into common representation spaces can help in the development of more sustainable food. Furthermore, incorporating active learning methods can steer new experimentation while incorporating adequate prior domain knowledge.

Who are we looking for?

We are looking for candidates with a PhD degree and demonstrable experience in the field of machine learning with a focus on representation learning; additional experience in the food sector and especially in food processing would be strong plus.

Our group and research- and what do we offer?

We offer a pioneering position that is part of a large collaboration between several departments within the University of Copenhagen and with leading international universities in the field. The postdoctorate Fellow will be positioned at the Computer Science department (located at the Universitetsparken Campus) but also be part of a growing group at the Food Science department (located at the Frederiksberg Campus) that will set up a significant effort on generating the data sets to be used in conjunction with the modelling. The postdoc is expected to bridge these two areas.

The Machine Learning Section is a part of the Department of Computer Science, Faculty of SCIENCE, University of Copenhagen and the ELLIS Unit Copenhagen (https://ellis.eu/). The department is heading two centers within Artificial Intelligence: the SCIENCE AI Center and the Pioneer Center within Artificial Intelligence.

The University of Copenhagen was founded in 1479 and is the oldest and largest university in Denmark. It is often ranked as the best university in Scandinavia and consistently as one of the top places in Europe. Within computer science, it is ranked number 2 in the European Union according to the Academic Ranking of World Universities (ARWU) 2021. Copenhagen is one of the 10 most livable cities in the world with a rich culture within music, theater and associations. Life for families is made easy by a publicly supported daycare and health care system, dual career opportunities, maternity/parental leave and six weeks of paid annual vacation. International candidates may find information on living and working in Denmark here. Useful information is also available at The International Staff Mobility office (ISM) at the University of Copenhagen (link). ISM offers a variety of services to international researchers coming to and working at the University of Copenhagen.

Principal supervisors are Prof Remko Boom, Remko.boom@food.ku.dk, and Prof Christian Igel, igel@di.ku.dk.

Co-supervisor is Tenure-track Assistant Professor Raghavendra Selvan, raghav@di.ku.dk

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Responsibilities and tasks

• Developing ML method for representation learning that allow to map the space of food ingredients and functional properties
• Developing methods for active learning that can process data collected by other team members and using this to steer further data collection
• Participate in a larger, multidisciplinary team of postdocs and PhD students
• Coordinate a part of the larger project together with the PIs
• Co-supervise PhD student(s) within the larger project, together with the PIs
• Write scientific papers aimed at high-impact journals

We are looking for the following qualifications:

• A PhD degree in a relevant field (machine learning or equivalent computer sciences)
• Experience in machine learning applied in the field of food technology and processing is a plus.
• An inquisitive mind-set with a strong interest in exploring new ways of experimentation and a willingness to work with people having different scientific backgrounds
• Good language skills in English (the professional language of communication); familiarity with the Danish language is not required but a plus.

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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), that describes your motivation for applying for the Fellowship
2. Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position
3. Original diplomas for MSc and PhD 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. Full publication list
5. Reference letters (if available)

Application deadline:

The deadline for applications is 30th June, 2025, 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 https://employment.ku.dk/faculty/recruitment-process/.

Interviews with selected candidates are expected to be held in weeks 30-31.

Questions

For specific information about the fellowship, please contact the principal supervisors.

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