Scientist

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.