Scientist - Ensemble Structural Informatics
Leads development of standards and validation frameworks for dynamic structural biology data, focusing on ensemble models from X-ray crystallography and cryo-EM. Collaborates with engineers to build deposition, search, and retrieval infrastructure for the diffUSE Project. Requires PhD in structural biology or related field.
Key Responsibilities
- Oversee 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
Required Skills and Qualifications
- 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
Preferred Skills and Experience
- 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
Bioinformatics Scientist
Independently provides bioinformatics and data science support, applying statistical genomics, machine learning, and scalable analysis of high-dimensional omics data to generate biological insights. Requires Ph.D. (or Master's) and 3+ years experience in bioinformatics or related quantitative field.
Data Scientist 1
Entry-level Data Scientist role focused on marketing data analysis, segmentation, attribution, and propensity modeling using SQL, Python, and cloud platforms. Collaborate with data engineers and clients to build analytics pipelines and deliver business insights.