About the Company:

Currently seeking a highly motivated and experienced computational scientist to join a dynamic biotech start up in San Diego. The successful candidate will lead innovative projects at the intersection of bioinformatics, machine learning, protein design , and experimental data analysis, contributing to groundbreaking advancements in biotechnology. This role requires a unique combination of technical expertise, strategic thinking, and collaboration with multidisciplinary teams.

About the Role:

Key Responsibilities:

• Develop and deploy scalable bioinformatics solutions to address complex biological questions.
• Design and train large language models (LLMs) for protein design and optimization, leveraging our unique capabilities to generate quantitative protein-protein interaction measurements at unprecedented scale.
• Implement and drive iterative learning cycles between computational bioinformatics and experimental workflows, such as active learning or reinforcement learning approaches.
• Analyze sequencing data from a variety of platforms, including Illumina, Oxford Nanopore, and PacBio, to extract meaningful insights.
• Collaborate closely with experimental scientists to refine models and validate predictions through laboratory experiments.
• Champion a high-quality, scalable code base by adhering to best practices in software development, including unit testing and continuous integration/continuous deployment (CI/CD).
• Mentor junior scientists and contribute to fostering a culture of innovation and excellence within the team.

Qualifications:

Required Skills and Qualifications:

• PhD in Computational Biology, Bioinformatics, Biophysics, Computer Science, or a related field with at least 5 years of relevant industry or postdoctoral experience.
• Proven expertise in Python programming, with a strong track record of developing scalable and efficient bioinformatics pipelines.
• Demonstrated experience in designing, training, and applying large language models to solve biological challenges, particularly in protein design.
• Familiarity with active learning, reinforcement learning, or other iterative learning paradigms in scientific contexts.
• Deep knowledge of sequencing technologies (Illumina, Oxford Nanopore, PacBio) and analysis methodologies.
• Exceptional problem-solving skills and the ability to translate complex biological problems into computational solutions.
• Excellent communication and collaboration skills, with a proven ability to work effectively within interdisciplinary teams.

Preferred Skills:

• Experience with cloud computing platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Apptainer).
• Proficiency in machine learning frameworks such as TensorFlow or PyTorch.
• Knowledge of structural bioinformatics and protein modeling tools.
• Familiarity with laboratory techniques and experimental validation processes.

Pay range and compensation package:

• $170,000 - $200,000
• Bonus
• Equity
• Healthcare

Equal Opportunity Statement:

Include a statement on commitment to diversity and inclusivity.