The Bernhard Nocht Institute for Tropical Medicine ( is the largest Research Institute for Tropical Medicine in Germany and is the National Reference Centre for Tropical Pathogens, a WHO Collaborating Centre, and a member of the Leibniz Research Association.
The Computational Infection Biology Department, led by Thomas Otto, is seeking a highly motivated PhD Student (in data science, m/f/d) - full-time, EG 13 TV-AVH.
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.
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.
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 workingenvironment that is free of prejudice.
Please apply by 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.
If you have any questions regarding the formal application process or the selection procedure, please contact Ms. Jeannette Meurer from the HR Department ( ).
For all other questions, please contact Prof. Thomas Otto -
#J-18808-LjbffrVeröffentlichungsdatum:
12 Mär 2026Standort:
HamburgEinsatzort:
Bernhard-Nocht-Str. 74, 20359 HamburgTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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