PhD Student (in data science, m/f/d) – full-time, EG 13 TV-AVH – Dpt. Computational Infection Biolog
PhD Student (in data science, m/f/d) – full-time, EG 13 TV-AVH – Dpt. Computational Infection Biolog
PhD Student (in data science, m/f/d) – full-time, EG 13 TV-AVH – Dpt. Computational Infection Biolog
PhD Student (in data science, m/f/d) – full-time, EG 13 TV-AVH – Dpt. Computational Infection Biolog
Bernhard-Nocht-Institut fuer Tropenmedizin Jobportal
Gesundheit, Soziales
Hamburg
- Art der Beschäftigung: Vollzeit
- Vor Ort
- Zu den Ersten gehören
PhD Student (in data science, m/f/d) – full-time, EG 13 TV-AVH – Dpt. Computational Infection Biolog
Über diesen Job
The
Computational Infection Biology Department
, led by Thomas Otto, is seeking a highly motivated
PhD Student (in data science, m/f/d)
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.
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.
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
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.
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.
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.
If you have any questions regarding the formal application process or the selection procedure, please contact Ms. Jeannette Meurer from the HR Department ( meurer@bnitm.de ).
For all other questions, please contact Prof. Thomas Otto - thomas.otto@bnitm.de .
If you have any questions regarding the formal application process or the selection procedure, please contact Ms. Jeannette Meurer from the HR Department ( meurer@bnitm.de ).
For all other questions, please contact Prof. Thomas Otto - thomas.otto@bnitm.de .
Unternehmens-Details
Bernhard-Nocht-Institut fuer Tropenmedizin Jobportal
Gesundheit, Soziales