AI BioHub Fellow

C10 Labs • Cambridge, MA

4d

About The Position

About C10 Labs C10 Labs is a venture studio and fund focused on building and backing AI-driven startups tackling critical challenges in healthcare, energy, industrial systems, and scientific discovery. Our team works hands-on with founders to co-create companies at the earliest stages, combining deep technical expertise with operational support and venture capital. Headquartered in Kendall Square at MIT, C10 Labs sits at the intersection of frontier AI research and company creation. We partner with leading institutions, operators, and investors to translate breakthrough research into high-impact startups. About the AI BioHub The AI BioHub is a collaboration between C10 Labs and LabCentral designed to accelerate the next generation of AI-enabled biotech companies. The program brings together AI researchers, computational biologists, drug discovery scientists, and venture builders to develop startups at the intersection of machine learning and the life sciences. The BioHub focuses on areas such as: AI-enabled drug discovery Computational biology and genomics Therapeutics development Bioinformatics and multi-omics analysis AI-driven clinical and translational research AI for lab automation and experimental design AI Fellows play a key role in helping founders translate advanced AI and biological insights into scalable startups. Position Overview We are seeking AI Fellows with expertise in life sciences and machine learning to join the AI BioHub. This is a part-time, cohort-based role designed for experienced researchers, engineers, and technical leaders who want to help build the next generation of AI-native biotech companies. AI Fellows work closely with founders, scientists, and venture builders to evaluate technical approaches, shape product and research strategies, and support the development of early-stage AI-driven biotech startups. This role is ideal for individuals with backgrounds in machine learning for biology, computational biology, drug discovery, or biomedical AI who want to engage directly in venture creation. What you'll do: Advise founders developing AI-enabled biotech and therapeutics startups Help evaluate and shape technical and scientific strategies for early-stage companies Provide guidance on AI model development and deployment in biological contexts Support teams working on areas such as drug discovery, protein modeling, genomics, and experimental design Collaborate with C10 venture partners and LabCentral leadership to identify promising scientific and commercial opportunities Share expertise through technical sessions, workshops, and office hours with cohort founders Help assess technical feasibility, scientific risk, and data strategy in AI-driven life sciences companies Stay connected to the broader AI, biotech, and academic research communities Ideal Background We welcome Fellows from both industry and academia with experience at the intersection of AI and the life sciences. Examples include: AI researchers applying machine learning to biology, chemistry, or drug discovery Computational biologists or bioinformaticians working with large biological datasets Scientists building AI-driven therapeutics platforms Engineers developing foundation models for biology or protein design Technical leaders from AI-native biotech startups Some expertise you may have: Product Development Experience: full product development and bringing cutting edge AI products, platforms, and services to market Technical Development: Expertise in AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and others. Strong programming full stack skills in languages such as Python, R, or Java, with experience in implementing machine learning models and algorithms. Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI solutions at scale. Familiarity with AI model optimization, including hyperparameter tuning, model evaluation, and performance benchmarking. Major plus will be experience with assessing tech readiness in AI projects using commonly used frameworks like TRL, AI Maturity Models, Model Validation Frameworks, SAFE AI, IEEE, IRL. Excellent communication skills and ability to explain complex AI concepts to non-technical stakeholders. What we offer: Expertise You May Have AI & Machine Learning Experience with ML frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn Experience building or deploying deep learning models for biological data Familiarity with generative AI, foundation models, or graph-based models in biology. Life Sciences & Bioinformatics Background in computational biology, genomics, proteomics, or structural biology Experience working with multi-omics datasets or biological data pipelines Familiarity with drug discovery workflows, target identification, or molecular modeling Experience integrating AI with wet-lab experimentation or lab automation Technical & Product Development Experience translating scientific research into products or platforms Knowledge of cloud infrastructure and ML deployment Familiarity with data engineering and scalable biological data pipeline Communication & Collaboration Ability to explain complex technical or scientific concepts to founders and investors Experience mentoring researchers, engineers, or early-stage teams

Requirements

• Expertise in AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and others.
• Strong programming full stack skills in languages such as Python, R, or Java, with experience in implementing machine learning models and algorithms.
• Knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI solutions at scale.
• Familiarity with AI model optimization, including hyperparameter tuning, model evaluation, and performance benchmarking.
• Excellent communication skills and ability to explain complex AI concepts to non-technical stakeholders.
• Experience with ML frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn
• Experience building or deploying deep learning models for biological data
• Familiarity with generative AI, foundation models, or graph-based models in biology.
• Background in computational biology, genomics, proteomics, or structural biology
• Experience working with multi-omics datasets or biological data pipelines
• Familiarity with drug discovery workflows, target identification, or molecular modeling
• Experience integrating AI with wet-lab experimentation or lab automation
• Knowledge of cloud infrastructure and ML deployment
• Familiarity with data engineering and scalable biological data pipeline
• Ability to explain complex technical or scientific concepts to founders and investors
• Experience mentoring researchers, engineers, or early-stage teams

Nice To Haves

• Major plus will be experience with assessing tech readiness in AI projects using commonly used frameworks like TRL, AI Maturity Models, Model Validation Frameworks, SAFE AI, IEEE, IRL.
• Experience translating scientific research into products or platforms

Responsibilities

• Advise founders developing AI-enabled biotech and therapeutics startups
• Help evaluate and shape technical and scientific strategies for early-stage companies
• Provide guidance on AI model development and deployment in biological contexts
• Support teams working on areas such as drug discovery, protein modeling, genomics, and experimental design
• Collaborate with C10 venture partners and LabCentral leadership to identify promising scientific and commercial opportunities
• Share expertise through technical sessions, workshops, and office hours with cohort founders
• Help assess technical feasibility, scientific risk, and data strategy in AI-driven life sciences companies
• Stay connected to the broader AI, biotech, and academic research communities

What This Job Offers

• Job Type: Part-time
• Career Level: Mid Level
• Education Level: No Education Listed