Scientist - Ensemble Structural Informatics (CURRENTLY NOT ACCEPTING APPLICATIONS)
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- onsite
- Employment
- FullTime
- Stated compensation
- USD 100,000–180,000 1 YEAR
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2 with evidence7 unclear or unstated- Remote policy
- onsite
“Provider workplace type: onsite”
From employer posting metadata - Degree requirement
- Required Skills and QualificationsPh.D. in structural biology, biophysics, computational biology, or related field
“Required Skills and QualificationsPh.D. in structural biology, biophysics, computational biology, or related field”
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- FullTime
- Compensation
- USD 100,000–180,000 1 YEAR
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Original job description
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Prism is seeking a Scientist to join a multidisciplinary team to help build the infrastructure needed to host and distribute dynamic structural biology data. Prism is a program within Radial, the basic life sciences division of the Astera Institute. We are making protein motion measurable, predictable, and actionable by building open infrastructure for studying protein dynamics directly from experimental data. Function emerges from the ensemble of conformations a protein adopts and how it moves between them, and we are rebuilding the structural biology stack around that premise: data collection, modeling, representation, and interpretation. We work at the interface of experimental structural biology (crystallography, cryo-EM), machine learning, computational biophysics, and open scientific tooling. Our team spans computational biologists, ML researchers, software engineers, and program staff, collaborating across Radial, Astera, and partner institutions.
This role will lead the development of standards that empower the structural biology community to deposit, validate, search, and leverage dynamic structural information at scale. A core focus will be establishing validation metrics and forward models for X-ray crystallography, cryo-EM, and related techniques, providing rigorous frameworks to assess the quality of structural models, distinguish geometric accuracy from fit to experimental data, and ensure scientific trustworthiness across diverse methodologies. This includes developing cross-modality validation metrics with a particular emphasis on ensemble and multistate models, where understanding which experimental data to validate against (i.e. raw images versus processed maps) and how such evaluations should be standardized and scaled within a database setting are open and consequential challenges.
The position involves architecting the foundational infrastructure alongside dedicated software engineers. Duties will also include building and socializing community standards to make dynamic structural biology data as accessible, reliable, and scientifically impactful as the Protein Data Bank has been for static structures. Your work will be central to evolving alongside algorithmic advances while upholding the highest standards of scientific rigor and reproducibility.
This is a full-time position within Prism, in-person at Radial, a division of the Astera Institute.
Key ResponsibilitiesOversee development of ensemble-aware validation frameworks that assess fit-to-data, physical realism, and uncertainty across diverse structural representations
Identify and prioritize technical challenges, from data representation to validation frameworks
Guide the creation of data deposition, search, and retrieval tools that allow users to interrogate and interpret structural heterogeneity at scale
Help coordinate with stakeholders to ensure interoperability and adoption
Work with software developers, data engineers, and user experience designers to translate scientific requirements into robust technical solutions
Ph.D. in structural biology, biophysics, computational biology, or related field
Demonstrated expertise in structural biology methods
Deep understanding of structural heterogeneity and dynamics in biomolecular systems
Experience with data standards, metadata frameworks, or scientific database development
Strong collaborative skills and ability to build consensus across diverse scientific communities
Experience with PDB, EMDB, BMRB, or other structural biology databases
Knowledge of validation methods for experimental and computational structural data
Familiarity with machine learning workflows and ML-ready data formats
Background in model uncertainty quantification or ensemble refinement methods
Understanding of software development practices and data engineering principles
Track record of working at the interface of methods development and infrastructure
The posted salary range is based on location in the Bay Area. The successful candidate will receive a competitive compensation package, commensurate with their experience and location.
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