Harmonize your Wet and Dry Lab. Backed by Lux.
About the role
We’re seeking an AI Biologist to join our Peptide Discovery team, pushing what AI can achieve in therapeutic peptide discovery. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- PhD in peptide chemistry, biochemistry, biophysics, structural biology, medicinal chemistry, or a related field
- Senior, hands-on peptide discovery experience: you have personally analyzed real program data, not just supervised it
- Deep expertise in at least one area (display and selection, biophysics, structural mapping, or peptide medicinal chemistry) and working fluency across the others
- Strong command of experimental design, quantitative data analysis in Python or R, and statistics
- AI-ready from day one: daily use of Claude, Cursor, or similar agents, with the judgment to spot where model reasoning is technically correct but scientifically unsound
- Confidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong
More about this role
Latch builds rigorous scientific benchmarks ( benchmarks.bio ) for AI agents across biology. We work with frontier labs and pharma to measure whether agents can handle real biological workflows: the messy, multi-layer reasoning that matters in the field.
We’re seeking an AI Biologist to join our Peptide Discovery team, pushing what AI can achieve in therapeutic peptide discovery.
About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert peptide discovery scientist. AI agents today struggle to interpret raw selection, biophysical, and structural data, to separate true hits from artifacts, and to make the calls that move a peptide from target to candidate. The data often misleads: enrichment can be a propagation artifact, protection is not contact, and binding is not function. Knowing what the evidence actually supports is the work. You will work with software engineers and scientists to build the tasks and datasets behind our benchmarks. They span linear, macrocyclic, and constrained peptides against protein targets, including protein–protein interactions, from target tractability to candidate nomination. Your judgment...
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