Jobs at Biohub

Manages the daily operation of an aquatic model-organism facility supporting scientific research. Oversees zebrafish and other aquatic species husbandry, water quality, recirculating systems, equipment maintenance, inventory, service contracts, EH&S compliance, facility upgrades, preventative maintenance, SOP documentation, and staff training. Collaborates with researchers, facilities teams, vendors, and safety consultants to ensure reliable operations, regulatory compliance, and animal welfare.

Develop and maintain scalable image-analysis pipelines for large fluorescent microscopy datasets; integrate multimodal data into AI-ready formats; improve segmentation, tracking, stitching, and registration; implement QC metrics and modular processing frameworks; collaborate with biologists and engineers and publish results.

Leads scaling of a live-imaging and data-generation pipeline for developing organisms. Responsibilities include setting throughput and quality targets, identifying bottlenecks, improving sample preparation and light-sheet microscopy, coordinating image-processing and compute workflows, establishing SOPs and QC gates, mentoring team members, and documenting open scientific methods. The role requires hands-on work across microscopy, biology, computation, and quantitative image analysis.

Lead AI safety research for biological applications: design safety evaluations, assess emerging capabilities, partner with scientists to build robust safeguards, inform policy, and communicate results to internal and external stakeholders.

Build and scale frontier AI systems for biology: design model architectures, run large-scale pretraining on GPU clusters, develop RL/reward modeling and multi-agent systems, create evaluation frameworks tied to biological outcomes, and publish/open-source research.

Manage daily wet-lab operations, inventory, equipment maintenance, and incident response. Develop and enforce safety protocols, SOPs, chemical and biohazard waste handling in coordination with EH&S. Identify operational risks, propose process improvements, support long-term lab planning, and provide general lab management support to scientists and platform leaders.

Develop and scale frontier AI systems for biology, including foundation models, pre-training pipelines, RL and multi-agent systems, evaluation frameworks, and community-facing publications and open-source releases to accelerate scientific discovery.

Lead and coordinate multidisciplinary imaging science and technology programs, develop and execute project plans, manage technical dependencies, track metrics and progress, communicate with stakeholders, mitigate risks, and document outcomes and best practices to deliver complex AIxBio and imaging initiatives aligned with the strategic roadmap.

Design and evaluate imaging data representations and tokenization strategies for biological AI models. Coordinate across experimental, data science, engineering, and research teams to prioritize data acquisition, define quality criteria, and combine heterogeneous modalities into robust training frameworks that improve model performance and scientific interpretability.