Senior Scientist I, Computational Biology
About The Position
GigaGen, a subsidiary of Grifols, is advancing transformative antibody drugs for immune deficiency, infectious diseases, and checkpoint-resistant cancers by leveraging industry-leading, single-cell technologies. GigaGen's novel technology platforms uniquely capture and recreate complete immune repertoires as functional antibody libraries. This approach has enabled the creation of first-in-class recombinant polyclonal antibody therapies for the treatment of infectious diseases. GigaGen's lead oncology asset, GIGA-564, is an anti-CTLA-4 monoclonal antibody that has demonstrated improved anti-tumor efficacy in vivo through a unique mechanism of action. GigaGen is leveraging its proprietary technology platforms for the continued discovery of novel recombinant polyclonal drugs and monoclonal antibodies to treat life-threatening diseases. GigaGen seeks a talented and highly motivated Senior Scientist, Computational Biology to support antibody therapeutics discovery, technology development and machine learning efforts. This is a broad computational biology role that combines supporting diverse bioinformatics and sequencing needs across research teams with independently leading computational research and technology development projects. The ideal candidate is a versatile scientist who enjoys solving biological problems, collaborating closely with experimental scientists, and applying modern computational and machine learning approaches where they can meaningfully advance the science.
Requirements
- PhD or Master's degree with significant relevant experience in Bioinformatics, Computational Biology, Genomics, Biology, Immunology, or a related discipline.
- A minimum of 5+ years of experience.
- Strong experience analyzing next-generation sequencing datasets and developing bioinformatics workflows.
- Strong proficiency in Python and/or R and in a Unix/Linux command-line environment, including shell scripting and common bioinformatics tools.
- Strong quantitative reasoning, statistical analysis, data visualization, and scientific interpretation skills.
- Experience applying machine learning to biological data, including supervised learning, model training and evaluation, and interpretation of model performance.
- Experience with protein language models, sequence embeddings, fine-tuning, and other modern approaches for modeling biological sequences.
- Experience or interest in applying computational approaches across diverse areas of drug discovery and technology development, such as target and antibody discovery, structural biology, proteomics, and high-throughput screening.
- Demonstrated ability to independently formulate computational approaches, critically evaluate and validate results, troubleshoot problems, and drive projects to completion with strong attention to data quality and reproducibility.
- Excellent communication and collaboration skills, including the ability to work effectively with experimental and multidisciplinary teams, manage multiple priorities, and proactively communicate progress, timelines, and challenges.
Nice To Haves
- Prior industry experience is preferred.
Responsibilities
- Analyze and critically interpret diverse biological datasets, including next-generation, long-read, single-cell, and antibody repertoire sequencing data.
- Provide computational expertise across research teams to address a broad range of bioinformatics and computational biology needs.
- Independently lead computational research and technology development projects, from defining scientific questions and strategy through analysis, interpretation, and experimental validation.
- Apply machine learning approaches to biological datasets, including predictive modeling and modern deep learning approaches for biological sequences.
- Evaluate and apply protein language models and other biological foundation models to address questions in antibody discovery and development.
- Develop robust, reproducible computational workflows for processing, analyzing, integrating, and visualizing biological data.
- Collaborate closely with computational and experimental scientists to design studies, interpret results, troubleshoot unexpected findings, and guide subsequent experiments.
- Clearly and proactively communicate project plans, progress, challenges, results, and recommendations to collaborators and stakeholders.
Benefits
- Medical
- Dental
- Vision
- life insurance
- PTO
- paid holidays
- up to 5% 401(K) match
- tuition reimbursement
- company bonus pool
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What This Job Offers
Job Type
Full-time
Career Level
Senior
