Senior Scientist , Computational Biology

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 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 antibody discovery and development
Develop robust, reproducible computational workflows for processing, analyzing, integrating, and visualizing biological data
Collaborate with computational and experimental scientists to design studies, interpret results, troubleshoot unexpected findings, and guide subsequent experiments
Communicate project plans, progress, challenges, results, and recommendations to collaborators and stakeholders
Support antibody therapeutics discovery, technology development, and machine learning efforts at Giga Gen

• 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
• Prior industry experience is preferred
• 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
• Ability to frequently drive to site locations with occasional travel within the United States

Expertise in Bioinformatics and Computational Biology with a strong focus on analyzing next-generation sequencing datasets and developing robust computational workflows. Proficient in applying machine learning techniques and protein language models to drive antibody discovery and technology development.

• Bioinformatics Workflow Development
• Next-Generation Sequencing Analysis
• Machine Learning Application
• Python and R Proficiency
• Statistical Analysis and Data Visualization

• Bioinformatics
• Computational Biology
• Next-Generation Sequencing
• Machine Learning
• Statistical Analysis
• Data Visualization
• Protein Language Models
• Unix/Linux Command-Line
• Shell Scripting
• Predictive Modeling

• Excellent Communication
• Collaboration Skills
• Problem-Solving
• Project Management
• Attention to Detail

• PhD or Master's Degree in Relevant Discipline

• Genomics
• Immunology
• Antibody Discovery
• Drug Discovery
• Structural Biology
• Proteomics
• High-Throughput Screening