PhD Student in data science

Our group develops computational approaches to understand host–pathogen interactions and their evolution, with the long-term goal of identifying new strategies for therapeutic intervention. This PhD project will leverage large-scale single-cell RNA-seq and spatial transcriptomics datasets from infection biology to develop models, including transformer-/graph-based models, that capture cellular responses to infection across tissues and conditions. The candidate will investigate systematic biases and biological confounders in existing datasets, develop computational strategies to correct or account for these biases, and build predictive models that simulate biological responses to in silico perturbations such as genetic or pharmacological interventions. The project aims to advance the use of foundation models for integrative, predictive modelling of host–pathogen systems. Core tasks of this position will include: Train, explore, and modify transformer-based models Characterize the nature, extend and impact of systematic biases and confounding variables and improve models to correct for these variables. Integrate multimodal data sources in the context of host-pathogen datasets Establish predictive pipeline for transfer learning and drug target discovery Apply models on pathogen and immunological datasets Provide bioinformatics support to other BNITM groups Contribute to teaching and training activities within the Otto group Contribute to project development and independent research initiatives Your profile: Completed master’s degree or equivalent in Computer Science, Bioinformatics or related fields with an interest in biology or Biological sciences with a strong background in programming Expertise and experience in programming, Python or R Expertise to work in a Linux environment Interest in biological questions and disease mechanisms Basic understanding of opportunities and limitations of LLMs and transformer models Experience with genomics or transcriptomics, next-generation sequencing analysis is a plus Expertise in AI/ML is a plus Experience with job submission systems/HPC is a plus Proficiency in English (oral and written) Excellent organisational skills and ability to plan and execute experiments independently and flexibly Strong team spirit and communication skills Creative mindset and strong problem-solving capabilities Proficiency in commonly used office software is expected (e.g. Office, Adobe is a plus) What we offer: An interesting and challenging job in a creative, supportive and highly motivated team An attractive, interdisciplinary research environment with state-of-the-art facilities Opportunities to realise independent research projects 30 days of vacation per year Flexible and family-friendly working hours Childcare subsidy Subsidy for HVV-ProfiTicket as “Deutschlandticket” (Basic) Company pension scheme Opportunities for further education and training Remuneration is paid in accordance with TV-AVH (collective agreement of the Hamburg Labour Law Association) in pay group EG 13. The position should start in Spring 2026 and is initially limited to 3 years. audit berufundfamilie - Zertifikat We support our employees in achieving a work-life balance and promote the professional equality of women, men and non-binary people. We strive to assist women in their scientific career, increase the number of women in research and reduce under-representation in all areas and positions in general. We explicitly welcome applications from people with disabilities. As a member of the Diversity Charter, the largest diversity management network in Germany, we are also committed to making diversity an integral part of our institute culture. It is our goal to create a working environment that is free of prejudice. Please apply by 25.03.2026 preferably online with the required documents (cover letter, CV, university certificates and your master project abstract/software project summary, as well as contact details of 2 references) via our online form.