Fellow - Frontier Research, AI Drug Discovery

2w2 weeks ago

Genentech

New York City, US · Full-time · $300,000 – $500,000

About this role

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) leverage these technologies to accelerate R&D. The Computational Sciences Center of Excellence harnesses data and AI to deliver innovative medicines for patients worldwide.

Frontier Research is a specialized unit dedicated to foundational machine learning research and new algorithmic frameworks. Operate within a flat scientific structure where senior scientists define their own research agendas. Leaders act as mentors shaping priorities across the organization.

Lead a frontier machine learning research lab with access to large-scale biological data, experimental collaborators, and high-performance computing resources. Pursue long-horizon, foundational research focused on enduring scientific influence. Commitment to open science, publication, and academic engagement is a core objective.

Shape the frontier of machine learning to transform biological understanding at scale. Mentor scientists as peers while preserving research autonomy. Recruit and develop emerging researchers into internationally recognized leaders through influential work.

Requirements

Globally recognized scientist in machine learning
Experience in foundational machine learning research for biology
Track record of sustained scientific influence and influential publications
Expertise developing new algorithmic frameworks
Commitment to open science and community contribution
Ability to lead in a flat scientific structure with peer mentorship
Familiarity with life-science research environments

Responsibilities

Lead a frontier machine learning research lab
Enable and support independent research at the leading edge of machine learning
Mentor scientists as peers, fostering rigorous discourse while preserving autonomy
Recruit and develop emerging machine learning researchers into global scientific leaders
Pursue long-horizon foundational research with focus on algorithmic frameworks
Leverage large-scale biological data and computing resources to impact drug discovery
Promote open science, academic engagement, and community contribution