Postdoc in Bioinformatics/Data Science/Machine Learning

Department of Drug Design and Pharmacology &
Center for Pharmaceutical Data Science Education
Faculty of Health and Medical Sciences
University of Copenhagen

We are looking for a highly motivated and ambitious bioinformatician / data scientist / machine learning specialist for a two-year Postdoc commencing 15th May 2025 or as soon as possible thereafter.

Principal supervisor
Associate Professor Alexander S. Hauser, Department of Drug Design and Pharmacology
E-mail (preferred): alexander.hauser@sund.ku.dk

Start: 15th May 2025

Duration: 2 years as a postdoctoral researcher

Our group and research
The explosion of biomedical data in genomics, structural biology, pharmacology, and related fields provides new opportunities to deepen our understanding of human physiology and disease. We integrate these data with innovative computational tools to gain novel insights into protein biology. Our strength is the combined expertise in selected biological systems with the integration of diverse, often unique datasets and hypotheses. The common objective of our projects is to gain insights into novel drug targets and to reveal fundamental principles in biological systems. The Hauser group consists of around ten members with a very international profile and provides a strong and ambitious research environment. The group has broad expertise encompassing structural bioinformatics, statistical genetics, cheminformatics, database development, and the application of machine learning approaches.

Job description
The position is part of an ambitious project titled "Nature-based solutions for biodiversity, human well-being and transformative change" as part of a EU-consortia spanning 14 partners (Biodiversity2Drugs) funded by the EU and the Innovation Foundation Denmark.

The overall Biodiversity2Drugs project aims to unlock the untapped potential of nature-derived drug discovery, enhancing European and global competitiveness through a sustainable and eco-friendly platform. By integrating advanced genomics, transcriptomics, peptidomics, AI/ML, green chemistry, and translational pharmacology, the project will efficiently discover and characterize novel pharmacological tools and therapeutic leads for various diseases. Its vision includes generating extensive sequence libraries of hundreds of thousands of nature-derived peptides from genomic and transcriptomic data. These peptides will be explored as novel GPCR ligands to improve drug discovery and study disease-related receptor signaling.

The genomic revolution has allowed researchers to generate and analyse genome-scale datasets to improve our understanding of fundamental ecological and evolutionary processes. However, little focus has been given on inter-species molecular interactions mediated by peptide: receptor couplings. Here, we want to comprehensively map the chemical space of all peptides found in bacteria, fungi, plants, and animal toxins, including cone-snails, snakes, and spiders. You will develop state-of-the-art comparative genomics and end-to-end deep learning pipelines to find inter-species and across-domains-of-life peptide:receptor pairs that have co-evolved for their respective ecological niche; potentially elucidating novel molecular interconnections between species retelling evolutionary processes. You will build and utilize end-to-end deep-learning protocols based on AlphaFold-based transformative models along with protein language models to predict, process, and analyze receptor-peptide interactions.

Profile
We are looking for a highly motivated and ambitious bioinformatician, data scientist, or machine learning specialist proficient with biologically driven questions, ideally experienced in protein-protein interactions and protein language models.

Essential experience and skills:

• An MSc and PhD related to bioinformatics, computational biology, computer science, machine learning, systems biology, pharmaceutical sciences, applied math/statistics/physics, data science, or related fields.
• Excellent programming skills, preferably in Python or R
• Experience handling (large) datasets, performing data parsing and analysis
• Proficient communication skills and ability to work in teams
• Excellent written and spoken English skills

Desirable experience and skills:

• Experience with machine learning / deep learning / protein language models
• Experience with software and pipeline design
• Experience mining publicly available genome and transcriptome data
• Experience working with protein structures and protein-protein interactions
• Knowledge of cell biology, protein structures, and evolution
• Code versioning with GitHub
• The applicant should be reliable and well organized. The work requires independence and demands flexibility and accuracy. Further, you must have good interpersonal skills and interest in working in an international team

The person will be required to relocate to Copenhagen and key responsibilities will include: establishing research ideas together with the principal investigator, leading the research project on a day-to-day basis, presenting research in internal meetings and international conferences, taking an active part in manuscript writing, and translating new knowledge in the subject area into research activity. There will be the opportunity to supervise more junior group members and contribute to teaching and dissemination activities.

Place of employment
The place of employment is at the of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen as well as the newly founded Center for Pharmaceutical Data Science Education (CPDSE). We offer creative and stimulating working conditions in a dynamic and international research environment. Our research facilities include a competitive computational core facility and modern environment. Moreover, we are part of the cluster for Integrated Structural Biology (ISBUC), Center for Health Data Science (HeaDS), Science AI Centre (AICenter), and the pharmaceutical informatics research section.

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. The starting date is 15th of May 2025 or as soon as possible thereafter.

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 40,781 DKK/approx. 5,467 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 2020.

Questions
For further information, applicants may contact the principal supervisor, Associate Professor Alexander S. Hauser, Department of Drug Design and Pharmacology, alexander.hauser@sund.ku.dk

The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.

Application procedure
Your online 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). Please mention why you are interested in the position and why this could be the right project for you.
• 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.
• References and recommendations
• Link to your GitHub account

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.

The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.

Department/Location: Department of Drug Design and Pharmacology & Center for Pharmaceutical Data Science Education