Computational Biology & Bioinformatics Lead

Sci.bio Recruiting; Boston (MA); On-site; USD 180,000 - 240,000; Full time

Job summary

Sci.bio Recruiting seeks a Computational Biology & Bioinformatics Lead to co-lead the computational protein science team. You will oversee ML and data systems supporting antibody and antigen discovery, protein characterization, neuroscience, lab automation, and operations.

The role trains and applies foundation models for protein structure prediction and design, builds models predicting biophysical properties from sequence and structure, and turns large multimodal datasets into usable tools and

Qualifications

• PhD in computational biology or related field with protein science focus.
• 5+ years of relevant experience including team mentoring.
• Strong Python and PyTorch experience in ML for biology.
• Experience with multimodal biological data and protein design.
• Track record in de novo protein/antibody design projects.

Responsibilities

• Train, fine-tune, and benchmark foundation models for protein folding and design, including structure prediction and generative models for de novo binder and antibody design, and deploy them for routine use in antigen and antibody discovery.
• Build and validate models predicting biophysical properties from multimodal data across sequence, structure, and omics datasets.
• Run in silico binder and antibody design campaigns and coordinate experimental cycles to improve models.
• Develop pipelines and platforms for in vitro antibody discovery data, proteomics, and sequencing analyses.
• Build and maintain web portals and databases for large biological datasets, including external catalogs like OpenAntigens.
• Collaborate with cross-functional teams to design experiments and integrate computational tools into workflows.
• Manage cloud/HPC environments, including GPU infrastructure for training and analyses.
• Lead and mentor a small team; present analyses to diverse audiences and contribute to patents/products.
• Define standards for data management, version control, reproducibility, and MLOps.

Skills

Team leadership

Python

PyTorch

Protein design

Multimodal data

Protein structure

Biochemistry background

Omics data

Education

PhD in computational biology / bioinformatics

Tools

GPU computing

Cloud platforms

Job description

The Computational Biology & Bioinformatics Lead will co-lead the computational protein science team, overseeing machine learning and data systems that support antibody and antigen discovery, protein characterization, neuroscience, lab automation, and operations.

The role focuses on training and applying foundation models for protein structure prediction and design, building models that predict biophysical properties from sequence and structure, and turning large multimodal datasets into usable tools and portals. This is a hands‑on technical and leadership position that works closely with the Associate Director & Program Manager of the Antibody Platform and reports to the Senior Director of the Antibody Platform.

Responsibilities

• Train, fine-tune, and benchmark foundation models for protein folding and design, including structure prediction and generative models for de novo binder and antibody design, and deploy them for routine use in antigen and antibody discovery.
• Build and validate models that predict biophysical properties such as stability, aggregation, expression, binding affinity, and developability, using multimodal data across sequence, structure, next generation sequencing, proteomics, and assay results.
• Run in silico binder and antibody design campaigns and coordinate experimental cycles so predictions are tested and results continuously improve the models.
• Develop pipelines and platforms for in vitro antibody discovery data, protein biophysical characterization, proteomics, and next generation sequencing analysis.
• Build and maintain web portals and databases for large biological datasets, including external antigen and antibody catalogs (e.g., OpenAntigens) and internal research databases.
• Collaborate with cross-functional teams to design experiments, interpret and analyze results, and integrate computational tools into established workflows.
• Manage cloud and high-performance computing environments, including GPU infrastructure for model training and large‑scale analyses.
• Lead and mentor a small team of computational biologists and bioinformaticians. Present computational analyses to technical and non-technical audiences and contribute to publications, patents, and products.
• Define standards for data management, version control, reproducibility, and MLOps within the group.

Required

Required Skills

• PhD in computational biology, bioinformatics, biophysics, machine learning, or a related field, with a strong background in protein science or biochemistry.
• 5 or more years of relevant experience, including experience leading or mentoring computational staff or serving as a technical lead. Direct experience managing a team of two to four people is a plus.
• Strong Python and hands‑on experience with deep learning frameworks such as PyTorch.
• Experience developing, modifying, and applying protein machine learning models for structure prediction and design.
• Experience building or training models on multimodal biological data, with a track record shown through publications, patents, or products.
• Experience with de novo protein and antibody design and validation cycles.

Preferred. (strong candidates will bring several of these, but not all are required)

• Experience with next generation sequencing analysis.
• Experience building data portals, APIs, or databases for large biological datasets.
• Experience with cloud computing and high‑performance computing or GPU environments.
• Familiarity with antibody discovery, proteomics, or protein biophysical characterization assays.
• Experience integrating computational predictions with wet‑lab workflows, including LIMS or ELN systems.