Founding ML Research Scientist - Biotech & Pharma

CT19, incorporated; New York (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

CT19, incorporated is seeking a Founding Research Scientist to lead modelling across live pharma and biotech projects. Turn scientific questions into model tasks, build training/evaluation plans, and deliver actionable findings for research teams.

This hands-on role offers substantial ownership, working closely with founders to decide which biological problems to tackle, data to generate, and how results become reusable capabilities.

Qualifications

• Direct experience training or substantially improving large models in biology or related domains.
• Strong judgement on representations, architectures, training objectives and evaluation.
• Hands-on experience with biological datasets and issues like noise and batch effects.

Responsibilities

• Lead modelling projects end to end: define questions, select data, train, evaluate and present results.
• Train and adapt models using diverse biological data including single-cell and imaging data.
• Develop models predicting cellular states and responses, including perturbations.
• Design rigorous evaluations with held-out experiments and independent cohorts.
• Collaborate with scientists to identify valuable data to acquire or generate next.
• Translate research into reusable model capabilities with engineering teams for scale.
• Explain results and modelling decisions clearly to ML and biology teams.

Skills

Large-model training

Biology data handling

Python

PyTorch or JAX

Multi-GPU experiments

Model evaluation

Perturbation models

Cellular imaging

Cross-species translation

PhD/postdoc experience

Education

PhD or equivalent research track record

Tools

PyTorch

JAX

Job description

CT19, incorporated is seeking a Founding Research Scientist to lead modelling across live pharma and biotech projects. Turn scientific questions into model tasks, build training/evaluation plans, and deliver actionable findings for research teams.

This hands-on role offers substantial ownership, working closely with founders to decide which biological problems to tackle, data to generate, and how results become reusable capabilities.