Postdoctoral positions at the Department of Biomedical Informatics & Data Science at Yale School of Medicine
New Haven, Connecticut (USA)
About the postdoctoral project
We are seeking several highly motivated postdoctoral researchers in computational immunology to work on exciting projects focused on the development of multi-scale models of the immune system, with a focus on B and T cell biology. The team has a strong focus on machine learning and interpretable deep learning. However, more theoretically oriented candidates, interested in developing mathematical and mechanistic models of the immune system, are also encouraged to apply. The projects can be tailored to the candidate’s skills and preferences in the following areas:
- Developing interpretable deep learning approaches to model T cell receptors and B cell receptor binding, as well as for analyzing and integrating multi-omics datasets.
- Creating hybrid mathematical-AI models that combine mechanistic knowledge with AI to tackle challenges related to data scarcity, robustness, and generalization in existing data-driven models.
- Investigating and addressing uncertainties in AI models by adapting current reliability benchmarks for single-cell dataset analysis.
- Developing multi-scale mechanistic or data-driven models of the immune system, with a focus on T and B cell biology.
Candidate requirements
Candidates must have a PhD in Computational Biology, Bioinformatics, Systems Biology, or a STEM-related field (e.g., Mathematics, Physics, Computer Science). Those in the final stages of their PhD are also eligible to apply. A good understanding of molecular biology and/or immunology is considered an asset. The successful candidate should be capable of working both independently and as part of a team.
- Essential skills:
- Proficiency and hands-on experience in machine learning and deep learning.
- Strong programming skills, preferably in Python.
- Solid foundation in mathematical modeling, probability, and statistics.
- Ability to work collaboratively in an interdisciplinary team.
- Good to have:
- Experience in computational biology.
- Familiarity with multi-omics data analysis.
- Knowledge of interpretable deep learning methods.
- Good understanding of immunology and/or molecular biology.
- Soft skills
- Excellent English, both written and spoken, and strong communication skills
- Ability to work effectively in teams
- Ability and interest in mentoring junior scientists
- Strong problem-solving and critical-thinking skills
- Good time management and organizational skills
- Ability to work independently and take initiative
About the Supervisor
The primary supervisor for the project is Prof. María Rodríguez Martínez, an Associate Professor in the Department of Biomedical Informatics & Data Science at the Yale School of Medicine. More about Prof. Rodríguez Martínez can be found here https://medicine.yale.edu/biomedical-informatics-data-science/profile/maria-rodriguezmartinez/.
About the department
The Department of Biomedical Informatics & Data Science (BIDS) is a new department at the intersection of health sciences and information technology. It develops new approaches to organize and analyze biomedical and healthcare data to promote health for all. More information about BIDS can be found https://medicine.yale.edu/biomedical-informatics-data-science/