5-7 years of relevant experience in machine learning and computational biology
Strong foundation in machine learning theory and practical implementation
Deep understanding of generative models relevant to scientific applications
Background in computational sciences, specifically biology and chemistry
MS or PhD in machine learning or related field preferred
Responsibilities
Develop generative models for protein conformational ensembles using data from simulations and experiments
Build innovative ML architectures for ensemble docking and generative chemistry applications
Adapt existing methods from literature to target intrinsically disordered proteins
Design scalable training pipelines to facilitate high-throughput experimentation
Collaborate with both computational and experimental scientists to ensure model validation against biophysical data
Benefits
Opportunities for interdisciplinary collaboration in cutting-edge research
Focus on high-impact projects in drug development
Engagement in innovative machine learning applications
Dynamic work environment with a focus on research and development
Full Job Description
We're seeking a research scientist to develop and optimize ML methods that bridge simulation, protein modeling, and small molecule design. This role requires both strong machine learning foundations and the ability to work at the interface of computational biology, structural modeling, and chemistry.
What you will do
Develop generative models for protein conformational ensembles trained on simulation and experimental data
Build novel ML architectures for ensemble-based affinity prediction and generative chemistry
Adapt methods from research literature to disordered protein targets
Design scalable training pipelines for high-throughput experimentation
Collaborate with computational and experimental scientists to validate models against biophysical data
What we are looking for
Strong foundation in machine learning theory and implementation
Deep understanding of modern generative models with application to the sciences
Background in computational sciences involving biology and chemistry
Preferred
MS or PhD in machine learning with application to computational science
Strong publication record
Experience with molecular simulation and protein modeling
