Scientist
Scientist building ensemble-aware protein representations and ML models that integrate dynamic structural data with PLMs, ligands, and functional info to advance dynamic structural biology. Requires PhD and experience with large bioinformatic pipelines.
About the job
Key Responsibilities
- Build ensemble-aware protein representations that integrate PLM and LLM embeddings with experimentally derived structural heterogeneity for functional prediction.
- Design, develop, and maintain large-scale bioinformatic pipelines capable of processing and managing complex, high-dimensional datasets.
- Fine-tune or architect ML models to capture sequence-structure-function relationships, with a focus on dynamic and conformational features.
- Synthesize diverse data sources spanning evolutionary history, binding affinity, allostery, and functional annotations to improve model performance and biological relevance.
- Collaborate closely with experimental partners to ground computational representations in real biological measurements and ensure models are continuously refined against experimental ground truth.
- Contribute to the broader diffUSE infrastructure, helping establish community-wide standards and tools for dynamic structural biology.
Required Skills and Qualifications
- PhD in bioinformatics, computational biology, machine learning, or a related field.
- Strong understanding of protein structure and function.
- Demonstrated experience building large bioinformatic pipelines and managing high-dimensional datasets.
- Proficiency in fine-tuning or modifying ML models (e.g., transformer-based architectures).
- Familiarity with protein language models (ESM, AlphaFold, etc.) is a plus.
- Collaborative, team-oriented mindset with the ability to drive research questions from conception to execution.
Skills
Bioinformatics, Computational Biology, Machine Learning, Protein Structure, Bioinformatic Pipelines, High-Dimensional Datasets, Transformer Models, Protein Language Models, Esm, Alphafold, Llm Embeddings
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