Postdoctoral Fellow-MSH-30040-230
About The Position
Details of Research Project: develop and apply machine learning models for antibody design and engineering, focusing on sequence–structure relationships, binding prediction, and optimization of antibody variants. The project integrates computational modeling with experimental protein engineering and immunological validation. Technical Duties: (include any protocols) Develop, train, and benchmark machine learning models for antibody sequence and structure analysis Perform large-scale computational analysis of antibody and nanobody repertoires Integrate structural modeling tools with ML-based prediction pipelines Assist with experimental validation workflows, including recombinant protein expression and binding assays Maintain documentation of computational workflows (HPC) and research protocols
Requirements
- PhD
- Experience in machine learning or statistical modeling
- Familiarity with protein structure, antibody engineering, or computational biology
- Experience with Python or similar scientific programming languages
- Ability to work collaboratively in an interdisciplinary research environment
Responsibilities
- Ongoing evaluation and treatment or research under the direct supervision of an M.D. or Ph.D.
- Neuropsychological assessments if appropriate to position.
- Cognitive remediation
- Individual supportive therapy.
- Group supportive therapy.
- Interdisciplinary team participation and coordination.
- Co-lead training seminars.
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What This Job Offers
Education Level
Ph.D. or professional degree
