Topos Bio is developing computational methods to drug intrinsically disordered proteins.
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 doDevelop 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
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
MS or PhD in machine learning with application to computational science
Strong publication record
Experience with molecular simulation and protein modeling
Skills Required
- 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
- MS or PhD in machine learning with application to computational science
- Strong publication record
- Experience with molecular simulation and protein modeling
What We Do
Topos Bio is an AI-powered biotechnology company developing therapies for intrinsically disordered proteins (IDPs) by creating an AI-native drug discovery platform that models protein ensembles to tackle previously undruggable targets.
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