The PREP Research Associate will contribute to a project on Machine Learning for Neutron Reflectometry, focusing on antimicrobial peptides (AMP).
Responsibilities include designing AI models to predict and generate peptides, developing data structures for AMP properties, validating AI frameworks, and guiding experimental measurements.
Qualifications: Ph.D. in relevant fields, 5+ years in machine learning applied to biochemistry, experience with NLP, graph neural networks, and platforms like PyTorch and TensorFlow.
Ideal candidates will have strong communication skills and U.S. citizenship is preferred.
Applicants must submit a CV (max 3 pages), along with personal details, and agree to background checks and vaccination requirements.
This role supports collaborative research under a federal program, emphasizing innovation in biomolecular AI applications.