Computational Biologist - AI/ML

A growing biotech-focused technology company is seeking a full-time scientist with expertise in computational biology or chemistry. This role involves developing and implementing novel computational strategies to support the design and refinement of macrocyclic peptide-based therapeutics. The ideal candidate will be a collaborative researcher who thrives in a multidisciplinary environment and is eager to contribute to the evolution of a cutting-edge computational platform.

Key Responsibilities

• Design and prototype new algorithms and workflows to streamline the discovery and enhancement of macrocyclic peptide candidates.
• Collaborate with machine learning specialists or independently lead data-driven modeling initiatives.
• Interpret experimental and computational data to guide platform improvements and inform scientific direction.
• Integrate both established and innovative computational tools into a production-ready software environment.
• Maintain and refine existing components of the platform to ensure scientific rigor, scalability, and robustness.
• Communicate progress clearly to team members and incorporate feedback from cross-functional collaborators.
• Actively contribute to a culture of continuous improvement, scientific excellence, and team-oriented problem-solving.

Required Qualifications

• Doctorate in a relevant scientific or computational field.
• Demonstrated experience in computational modeling of peptides, biologics, or small molecules.
• Proficiency with at least one molecular modeling or simulation toolkit (e.g., Rosetta, PyRosetta, RDKit, GROMACS, AMBER, OpenMM, GAMESS).
• Strong programming skills in Python, with familiarity in libraries such as NumPy, SciPy, Pandas, BioPython, and scikit-learn.
• Experience working in collaborative codebases using version control systems like Git.
• Eagerness to learn new tools and approaches to tackle complex scientific challenges.

Preferred Experience

• Development or training of AI/ML models for molecular property prediction or generative design.
• Prior work in the biotech or pharmaceutical industry.
• Background in cyclic peptide modeling, including docking, scoring, or de novo design.
• Familiarity with Linux environments, SQL databases, and cloud infrastructure (e.g., AWS, GCP, Azure).
• C++ development experience, especially in the context of molecular modeling frameworks.
• Knowledge of free energy calculations or hybrid quantum/classical simulation techniques.