General DiffUSE Job Application
Open general application for computational biology, ML research, data science, software engineering, and program roles at DiffUSE, focused on protein dynamics, structural data infrastructure, and open science tooling.
About the job
Role Categories We're Actively Building Around
Computational and data science
- Diffraction data processing and structural data pipelines
- Multiconformer and heterogeneity analysis from large datasets
- Data standards work (mmCIF and related)
- Macromolecular ensemble metrics
- Machine learning research for macromolecules and biophysics
- Representation learning for protein dynamics
- ML on raw experimental data rather than processed structures
- 3D vision and geometric deep learning backgrounds especially welcome
- Dataset generation and open release
- Designing and running campaigns to generate large structural datasets
- Partnering with external collaborators to open and standardize existing datasets
- Bridging experimental facilities, data producers, and the open-science community
Software and infrastructure engineering
- Scientific data infrastructure, pipelines, and tooling
- Open-source release engineering, reproducibility, and developer experience
Program and operations
- Program management, scientific coordination, communications
- Open-science publishing and community building
What We Look For Across All Roles
- Familiarity with protein biophysics and the experimental methods that generate structural data
- High agency: you identify what needs doing and move it forward without waiting for direction
- Ability to drive projects and people, including collaborators outside your reporting line
- Comfortable owning a problem end-to-end and unblocking collaborators
- Strong commitment to open science and public-good infrastructure
- Comfort working at the boundary between disciplines
- Bias toward shipping, iteration, and rapid feedback
- Clear written and verbal communication
- Track record of independent work inside collaborative teams
Skills
Machine Learning, Structural Biology, Cryo-Em, Crystallography, Computational Biophysics, Data Pipelines, Open Source, Mmcif, Representation Learning, Geometric Deep Learning
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