ML Researcher - Multimodal Biotech AI for Silico Discovery

GC Therapeutics, Inc.; Cambridge (MA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

PTO

Holidays

Medical Insurance

Dental Insurance

Vision Insurance

401(k)

Life Insurance

Disability Insurance

Transportation Subsidy

Job summary

GC Therapeutics is seeking a Machine Learning Researcher to design, train, and benchmark virtual cell models for its in silico discovery platform. You will work hands-on with senior scientists and experimental biologists to translate model predictions into therapeutic hypotheses.

The role emphasizes building deep learning pipelines, processing multimodal datasets (scRNA-seq, perturbations, ATAC-seq, imaging), and collaborating across teams.

Qualifications

• MS + 2‑3 years of experience or PhD in computer science, machine learning, computational biology, or related field.
• Deep understanding of machine learning and deep learning approaches and their application to real world problems. Proven expertise in developing, implementing, and training state‑of‑the‑art deep learning models (autoregressive models, transformers, LLMs, VAEs, or related architectures).
• Strong experience processing and analyzing large-scale multimodal datasets.
• Proficiency with Python (Numpy, Scipy, Pandas, sklearn) and modern deep learning frameworks (PyTorch, JAX).
• Experience with large‑scale model training on GPUs and distributed systems.
• Strong work ethic with the ability to perform tasks independently.
• Proficient in analysis, presentation, and documentation of scientific data and scientific reports.
• Effective communicator with excellent interpersonal skills.
• Strong project management and organizational skills and ability to prioritize and multitask.

Responsibilities

• Design and train deep learning architectures for modeling perturbation response and cellular state from multimodal training data.
• Build and maintain benchmarking pipelines to evaluate model performance and generalization.
• Process and integrate large-scale multimodal biological datasets (single-cell RNA-sequencing, perturbation, single-cell ATAC-seq, imaging) into training‑ready pipelines.
• Collaborate with experimental biologists to define modeling tasks and validate predictions against wet‑lab data.

Skills

Deep learning models

Multimodal data processing

Python (NumPy, Pandas)

PyTorch/JAX

GPU/Distributed training

Independent work

Communication

Education

MS + 2-3 years or PhD in CS/ML/Computational Biology

Tools

PyTorch

JAX

NumPy

Pandas

Job description

GC Therapeutics is seeking a Machine Learning Researcher to design, train, and benchmark virtual cell models for its in silico discovery platform. You will work hands-on with senior scientists and experimental biologists to translate model predictions into therapeutic hypotheses.

The role emphasizes building deep learning pipelines, processing multimodal datasets (scRNA-seq, perturbations, ATAC-seq, imaging), and collaborating across teams.