C
Computational Biologist
Not specifiedFull-timeData ScienceBiotechnologyPharmaceuticals
Join a biotechnology research team developing computational methods for therapeutic antibody design, optimization, and multi-omics analysis.
Responsibilities
- Design and optimize multispecific therapeutic antibodies using computational and AI models.
- Translate engineering concepts into experimentally validated antibody candidates.
- Collaborate with computational biologists and antibody discovery scientists.
- Coordinate with external CROs on antibody design and optimization projects.
- Evaluate and develop methods that expand computational antibody design capabilities.
- Perform end-to-end computational analyses of multi-omics datasets for target analysis.
- Communicate scientific results and design rationale to internal and external audiences.
Requirements
- M.Sc. or Ph.D. in bioinformatics, computational biology, structural biology, protein engineering, or a closely related field.
- Three to five years of relevant experience in the biotechnology or pharmaceutical industry.
- Hands-on experience with antibody developability and optimization, including humanization, sequence liability assessment, immunogenicity, structural prediction, and epitope prediction.
- Proficiency with protein modeling tools such as PyMOL.
- Familiarity with current AI-based models for antibody design and sequence optimization.
- Proficiency in Python or another scripting language for data analysis.
- Experience with foundational models and LLM-based coding agents.
- Familiarity with multi-omics datasets and analysis.
- Excellent written and verbal English communication skills.
Nice to have
- Background in biochemistry or structural biology.
- Hands-on experience analyzing single-cell RNA, RNA-seq, or proteomics data.
- Knowledge of immuno-oncology or cancer biology.
- Familiarity with public cancer atlas datasets such as TCGA and GTEx.
- Track record of scientific publications.