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Salary: USD 155,000 - 215,000 / annual
Alta Resource Technologies is a synthetic biology company founded in 2023 that uses computational and experimental approaches to extract critical minerals from conventional, unconventional, and waste sources (e-waste). The company is addressing a historic supply-chain challenge driven by exponential growth in mineral demand from tech and IT sectors.
The Head of Computational Biology will lead a small team of computational scientists while remaining a hands-on individual contributor. This is a player/coach role combining technical execution with people leadership.
Key responsibilities include:
**Computational Model Development**: Lead the team in developing classification models and scoring systems for protein and chemistry candidates using in silico and real-world data. Establish molecular dynamics and quantum mechanics workflows for protein scoring. Execute workflows personally, contributing code and analysis alongside the team. Define success metrics tied to commercial outcomes (experimentally confirmed hits, manufacturable leads, candidates advancing toward commercialization) rather than model benchmarks alone. Build pipelines from sequence databases and 3D modeling data. Implement model fine-tuning using high-throughput performance data. Leverage protein manufacturing data to predict scalable production candidates. Deploy generative AI approaches to streamline workflows.
**Data Integration and Tracking**: Collaborate with the data science team to implement genotype-to-phenotype relationship tracking to complete the design-build-test-learn cycle. Build a world-class tracking system for proteins across design, build, test, and scale workflows. Leverage sequencing, production, and performance data to create a state-of-the-art multiscale protein and genome engineering system. Partner with build and test teams to integrate computational workflows, ensuring designs account for real-world constraints (throughput, cost, turnaround time).
**People Leadership**: Hire, directly manage, mentor, and develop a small team of computational scientists. Set clear goals and hold the team accountable for delivery. Balance hands-on contribution with team leadership. Ensure excellent documentation practices. Communicate results effectively across the company. Develop talent through team building and foster collaboration between computational, build, and test teams.
**Requirements**:
- Ph.D. in computational biology, bioinformatics, or related field with 5–10 years of proven success in cross-functional leadership
- Demonstrated people leadership: directly managing, hiring, and developing a team of scientists while remaining a hands-on individual contributor (player/coach)
- Proven track record of delivering outcomes: has built design/test systems that delivered protein, peptide, antibody, or similar candidates that were commercially relevant and advanced toward commercialization
- Expertise in machine learning and predictive models focused on protein engineering workflows
- Expertise in bioinformatics pipelines and databases
- Experience with generative AI models
- Experience with molecular dynamics and quantum mechanics parameterization
- Experience with LIMS and sample management systems
- Demonstrated knowledge of experimental design, the scientific method, and statistical analysis
- Demonstrated capabilities for building well-documented and version-controlled data pipelines
- Strong written and verbal communication skills and ability to work within different teams
- Strong organizational and documentation skills
**Desired qualifications**:
- Experience working within or alongside the build and test functions, not only design and learn
- Experience integrating computational workflows with laboratory automation and high-throughput build/test platforms
- Experience with multiomics data pipelines, flux balance analysis, and metabolic pathway modeling
- Experience with antibody engineering simulation pipelines
- Experience with Git, AWS, and standard computational tools
