Postdoctoral Fellow: Computational Protein Design and Machine Learning

About this position

Postdoctoral Fellow: Computational Protein Design and Machine Learning

• The Division of Pulmonary, Critical Care and Sleep Medicine at the
• University of Maryland, Baltimore, School of Medicine is seeking a
• postdoctoral fellow with expertise in computational protein design,
• structural bioinformatics, or machine learning for molecular
• engineering. The fellow will work closely with experimental
• researchers to design and optimize therapeutic proteins, nanobodies,
• receptor-binding molecules, and imaging agents.

Key Responsibilities

• Apply protein structure prediction and computational design methods to generate and prioritize candidate molecules.
• Analyze protein–protein interactions and sequence–structure–function relationships.
• Integrate relevant biological datasets to inform target selection and molecular design requirements.
• Collaborate closely with experimental team members so that computational predictions are tested and experimental data feed directly back into design.
• Contribute computational and analytical support across the lab’s broader research program as needed.
• Present findings at internal meetings and scientific conferences and prepare manuscripts for highimpact journals.
• Mentor junior researchers and contribute to a collaborative lab environment.

Qualifications

• PhD in Computational Biology, Bioinformatics, Biophysics, Chemistry, Computer Science, or a related field.
• Demonstrated experience with modern protein structure prediction and design tools, including AlphaFold2/AlphaFold3, Boltz, or Chai-1 for structure and complex prediction; RFdiffusion, ProteinMPNN, or Rosetta for design and inverse folding; and ESM-family or other protein language models.
• Proficiency in Python and scientific computing is expected.
• Experience with molecular dynamics simulation (GROMACS, OpenMM, or AMBER) and structural analysis of protein-ligand interactions.
• Experience analyzing deep mutational scanning, directed evolution, or other high-throughput sequencing datasets is desirable.
• A track record of computational designs that were experimentally validated, or prior experience working alongside a wet lab, is a strong plus.
• Ability to work independently and within a collaborative team; strong communication and writing skills.

• Application: Interested candidates should send their CV, a cover
• letter outlining their research experience, interest in this position
• and contact information for three references to Dr. Nalinikanth
• Kotagiri at NKotagiri@som.umaryland.edu

Desired start date: Immediately