Modeling Engineer​/Scientist

About Fulcrum

Fulcrum Neuroscience is a biotech startup developing new therapeutic approaches to Alzheimer's disease and other neurodegenerative conditions. At the heart of Fulcrum's approach is a unique computational platform: the Brain Health and Neurodegeneration (BHN) world model, reconciling over 1,800 literature and data sources, and an underlying AI-enabled, digital twin computational engine. This platform enables Fulcrum scientists to explore target and therapeutic alternatives, identify biomarker patterns, and design lab and clinical experiments.

The BHN model is an explicit, mechanistic, causal representation of brain homeostasis and neurodegeneration - grounded in mass balance, energy flow, and feedback loops, and built to interpret experimental and clinical data rather than merely fit it. It functions as a structured, evolving repository of biological knowledge, enabling simulation of disease progression, digital twin inference, and population-level insight.

Reporting to the Chief Technology Officer, you will help expand and deepen the BHN model and continue to develop the AI-driven platform that builds it. This is a hands-on modeling role at the intersection of computational biology, systems engineering, and applied AI - a bridge between the science and the engineering.

Your work will include:

• Extending the depth and breadth of the BHN model, including expansion into additional neurodegenerative diseases.
• Developing and refining ODE-based mechanistic models of biological processes, from equations and level of abstraction through to integrated modules.
• Using the BHN model to analyze target opportunities, support therapeutic development and optimization, and design experiments for the lab and for clinical trials.
• Collaborate with software developers in the AI-driven workflows and tooling that accelerate model development and analysis, including chat and visualization interfaces, to enable modelers and scientists to interact with BHN.
• Creating clear annotations and documentation of model and software architecture and code.

This is an opportunity to work with pioneers in biological modeling and quantitative systems pharmacology (QSP) to make an impact on the treatment of neurodegenerative disease while working at the leading edge of modeling techniques and technology infused with AI.

The ideal candidate would be based in the San Francisco Bay Area and able to travel to the company's office in South San Francisco, CA one day per week. Remote candidates should be willing to travel to South San Francisco, CA every 1-2 months.

Required

• Advanced degree (PhD, or MS with relevant experience) in systems biology, biomedical or chemical engineering, computational biology, applied mathematics, or a related quantitative discipline. Open to candidates coming directly from a PhD or postdoc.
• Demonstrated experience developing ODE-based models of complex nonlinear systems.
• Hands-on experience using AI tools to support model development and analysis.
• Strong scientific communication skills and the ability to work across the science-engineering boundary.

Highly Desired

• Demonstrated experience developing ODE-based biological models.
• Familiarity with Bayesian inference, management of structural and parametric uncertainty and variability, in complex dynamic models.
• Experience with AI-assisted coding (vibe coding) and skill development for agentic workflows.
• Experience with Mathematica.
• Experience working in a pharma or biotech organization.
• Familiarity with neurodegeneration, aging biology, or brain physiology.

• The chance to shape a first-of-its-kind mechanistic, causal model of brain health at an early-stage company.
• Co-authorship on publications emerging from your contributions.
• Meaningful early-stage equity and contract rate commensurate with experience.

This is a full-time, contract-to-hire role: we intend it as a path to full-time employment.