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Head of Biology

You'll own biology end-to-end, working closely with founders and ML team .

About Bindwell

We're discovering new pesticides using AI. Pesticide usage per acre has doubled in the past 20 years, but we still lose 20-40% of crops to pests. Resistance is growing and fewer new solutions are introduced each year, with R&D costs mounting. We need a better way to discover new, safe pesticides. Backed by Y Combinator, General Catalyst, SV Angel, and Paul Graham, we've built top binding models for in-silico screening and generative molecular design, plus a fast assay pipeline for validation of new molecules. Our first AI-designed candidate attacks Spodoptera frugiperda via a new mode of action, and we're just getting started. Join our small team for the once-in-a-lifetime opportunity to reimagine how pesticide R&D is done, and make a lasting positive impact on humanity.

We don't care about age, pedigree, or which school you went to. We want excellent people capable of doing exceptional things. Years of experience often indicates strong ability, but so does being incredibly smart and driven. What we're building requires new thoughts and ideas, we need people who question assumptions and think from first principles. The most dangerous thing you can say is "We've always done it this way."

San Francisco, CA / Hybrid Full-time $100k - $160k + equity

Job Description and Responsibilities

We're looking for an exceptional scientist to help build the future of pesticide R&D. You will help design a pesticide discovery pipeline centered around machine learning, designing automatable, fast and easy assays that generate data conducive to ML model training. You will help ensure the safety and efficacy of the molecules we produce. You'll lead efforts in finding new molecular targets and leading the development of entirely new pesticides. This is a high-impact, cross-functional role for someone who's fast and wants to build the next generation of pesticides.

  • Design and carry out various pesticide efficacy and safety assays.
  • Help ML team develop toxicity screening models
  • Identify and validate new molecular targets and modes of action.
  • Manage external lab work, CROs, and vendor coordination.
  • Run internal ML models, MD simulations, and docking for in-silico screens and benchmarking.
  • Assess and build tools to assess resistance risk of new pesticides.
  • Guide all biological aspects of developing current and future pesticides.

Required Qualifications

  • Expertise designing & executing various toxicity, efficacy, and biochemical assays in a laboratory setting.
  • Solid foundation in mathematics, statistics, software engineering principles, and data science.
  • Extremely strong foundation in biochemistry, systems biology, and omics, with deep intuitive understanding of biological mechanisms and interactions.
  • Execution-oriented, intellectually flexible leader able to thrive and learn in an ambiguous, fast-moving startup environment with high ownership and low oversight.

Nice to Have

  • Experience with animal safety models (e.g., bee cell lines).
  • Experience with resistance-risk assessment.
  • Experience using molecular dynamics (GROMACS, FairChem's UMA, etc) and docking (AutoDock Vina, etc) tools.
  • Experience writing python code and using data science tools (pandas, numpy, scikit-learn, etc).
  • Experience managing CROs and vendors.
  • Knowledge of toxicology datasets and ML-based toxicity modeling approaches.
  • Understanding of ML fundamentals including neural networks, generalization, embedding spaces, and data biases.
  • Experience with advanced biochemical assay techniques (BLI, SPR, enzyme inhibition assays).

Basics

Experience

Research Experience

Short Answer Questions

Concisely describe why you picked the goal, what made it ambitious, your confidence level throughout, the specific things you did to pursue it (use technical detail), the outcome (success/failure), and what you learned. Quantify things whenever possible.
Clearly and concisely explain the problem and context around it (don't dumb things down if it's technical), what exactly made it hard for you, your initial understanding and confidence level, and most importantly how exactly you solved it. Include non-confidential concrete methods, thought processes, tools, innovations, quantifications, etc.
Write 3-4 sentences about something relevant to this position that demonstrates your exceptional ability. Express problem and solution. Quantify impact, use verbs, and be specific.

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