PhD Student in Data Science – Computational Infection Biology

The Bernhard Nocht Institute for Tropical Medicine, Germany's largest research institute for tropical medicine and a WHO Collaborating Centre, offers a PhD position in the Computational Infection Biology Department led by Prof. Thomas Otto. The department focuses on developing computational approaches to understand host–pathogen interactions and their evolution, aiming to identify new strategies for therapeutic intervention. This PhD project centers on leveraging large-scale single-cell RNA-seq and spatial transcriptomics datasets from infection biology. The successful candidate will develop and refine transformer- and graph-based models to capture cellular responses to infection across tissues and conditions. Key tasks include investigating systematic biases and biological confounders in existing datasets, creating computational strategies to correct these biases, and building predictive models that simulate biological responses to in silico perturbations such as genetic or pharmacological interventions. The project aims to advance foundation models for integrative, predictive modelling of host–pathogen systems. Core responsibilities involve training, exploring, and modifying transformer-based models, characterizing and correcting systematic biases and confounding variables, integrating multimodal data sources, establishing predictive pipelines for transfer learning and drug target discovery, applying models to pathogen and immunological datasets, providing bioinformatics support to other BNITM groups, and contributing to teaching and independent research initiatives within the Otto group. Applicants should hold a master’s degree or equivalent in Computer Science, Bioinformatics, or related fields with an interest in biology, or in Biological sciences with strong programming skills. Required expertise includes programming (Python or R), Linux environment proficiency, and a basic understanding of LLMs and transformer models. Experience with genomics or transcriptomics, next-generation sequencing analysis, AI/ML, and HPC/job submission systems is advantageous. Proficiency in English, excellent organisational skills, independent and flexible experiment planning, strong team spirit, communication skills, creativity, problem-solving abilities, and proficiency in office software are expected. The institute offers a creative, supportive, and highly motivated team environment, interdisciplinary research with state-of-the-art facilities, opportunities for independent research projects, 30 days of vacation per year, flexible and family-friendly working hours, childcare subsidy, HVV-ProfiTicket subsidy, company pension scheme, and further education and training opportunities. Remuneration is paid in accordance with TV-AVH pay group EG 13. The position is full-time, starts in Spring 2026, and is initially limited to three years. BNITM is committed to diversity, equality, and inclusion, supporting work-life balance and professional equality across genders and backgrounds. Applications from people with disabilities are explicitly welcomed. The institute strives to create a prejudice-free working environment and is a member of the Diversity Charter. Applications should be submitted online by 25.03.2026, including a cover letter, CV, university certificates, master project abstract/software project summary, and contact details of two references. For questions about the application process, contact Ms. Jeannette Meurer ([email protected]). For scientific inquiries, contact Prof. Thomas Otto ([email protected]). For more information and to apply, visit: Application Link .