AI Neuroscientist

LatchBio
San Francisco, CA
On-site

Who this role is best for

Best suited to candidates with neuroscience expertise and a strong grasp of AI evaluation working in AI benchmarking and research.

Best fit for

  • Candidates with deep neuroscience domain knowledge and experience in multi-modal data analysis
    — “Curate multi-modal data bundles (electrophysiology, calcium imaging, EEG/sEEG, MRI/PET, single-cell and spatial transcriptomics, histopathology, behavior, biofluid markers)”
  • Individuals who can act as a scientific gatekeeper for AI reasoning and confidently challenge model outputs
    — “Confidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong”
  • Candidates with a publication record and hands-on research experience in neuroscience
    — “Hands-on neuroscience research experience with first-hand data analysis and a publication record”

Things to consider

  • The role requires a strong commitment to full-time work with a preference for onsite presence in San Francisco
    — “Location: remote (anywhere), hybrid, or onsite in SF. We prefer onsite.”
  • No visa sponsorship is available, and the role is limited to US citizens, permanent residents, and OPT holders
    — “Work authorization: US citizens, permanent residents, and OPT holders. We can’t support STEM OPT extensions or sponsorship.”

How to stand out

  • Emphasize your ability to define expert reasoning and create gold-standard answers for neuroscience tasks
    — “Define what expert reasoning looks like for a research question or R&D decision, and write gold-standard answers with the rationale an experienced neuroscientist would defend”
  • Showcase your experience with model systems and their limitations in translating findings to human disease
    — “Test whether agents choose the right model system and unit of analysis, and recognize when rodent, iPSC, or organoid findings will not translate to human disease”
  • Highlight your ability to identify when AI reasoning is technically correct but scientifically unsound
    — “Proficiency in AI agent use, with the judgment to identify where model reasoning is technically correct but scientifically unsound”
  • Demonstrate your capability to adjudicate contested scientific claims using data and evidence
    — “Adjudicate contested claims in the literature: decide what the data supports, what they do not, and which experiment would settle the question”
  • Demonstrate your ability to calibrate confidence and communicate uncertainty in scientific evaluation
    — “Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • building rigorous scientific benchmarks for AI agents
  • testing AI agents in real biological workflows
Typical background
PhD or MD/PhD in neuroscience or a closely related field

Skills & requirements

Required

NeuroscienceAI Agent UseExperimental DesignStatisticsMulti-modal Data AnalysisScientific Benchmarking

Preferred

Hands-on Experience In Electrophysiology, Optical Imaging, Eeg/seeg, Neuroimaging, Single-cell Or Spatial Omics, Neuropathology, Or Quantitative Behavior

Stack & domain

NeuroscienceAIElectrophysiologyOptical ImagingEeg/seegNeuroimagingSingle-cell Or Spatial OmicsNeuropathologyQuantitative BehaviorExpert ReasoningJudgmentExperimental DesignStatisticsAI Agent UseOverrule An AI AgentBiological WorkflowsAI Agents

About the role

Original posting from LatchBio via Ashby

AI Neuroscientist

Latch builds rigorous scientific benchmarks (benchmarks.bio http://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 Neuroscientist to join our Neuroscience team, pushing what AI can achieve in neuroscience.

About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert neuroscientist. AI agents today struggle to interrogate raw evidence across molecular, cellular, circuit, tissue, and behavioral levels, separate real effects from artifacts and confounds, and reach conclusions and R&D decisions an expert would stand behind. You will work with software engineers and neuroscientists to build the tasks and datasets behind our benchmarks across normal nervous-system function and disease; your judgment will set the standard agent outputs are held to, including:

Build the task

  • Define what expert reasoning looks like for a research question or R&D decision, and write gold-standard answers with the rationale an experienced neuroscientist would defend
  • Design realistic research scenarios across the workflow, from hypothesis and target selection through model-system choice, experimental design, data processing, and inference
  • Curate multi-modal data bundles (electrophysiology, calcium imaging, EEG/sEEG, MRI/PET, single-cell and spatial transcriptomics, histopathology, behavior, biofluid markers)
  • Pair basic-science and disease tasks (e.g., hippocampal replay in health and its disruption in epilepsy or Alzheimer’s disease) to test whether an understanding of normal function transfers to pathology
  • Partner with software engineers to turn your judgment into new workflows

Set the hard calls

  • Test whether agents choose the right model system and unit of analysis, and recognize when rodent, iPSC, or organoid findings will not translate to human disease
  • Adjudicate contested claims in the literature: decide what the data supports, what they do not, and which experiment would settle the question

Judge the agent

  • Interrogate agent reasoning step by step, and challenge conclusions that are fluent and textbook-correct but would not survive lab meeting, peer review, or a go/no-go decision
  • Pinpoint where agents go wrong: state why a step fails, what an expert would do instead, and what evidence would change the call
  • Score agent confidence, rewarding explicit uncertainty over overconfident binary calls when evidence is incomplete

Requirements

  • PhD or MD/PhD in neuroscience or a closely related field
  • Hands-on neuroscience research experience with first-hand data analysis and a publication record
  • Direct experience analyzing raw data in at least two modalities: electrophysiology (patch-clamp, MEA, Neuropixels), optical imaging, EEG/sEEG, neuroimaging, single-cell or spatial omics, neuropathology, or quantitative behavior
  • Deep expertise in at least one area (systems/circuit, cellular/molecular, clinical/translational, or computational neuroscience) and working fluency across system levels
  • Strong command of experimental design and statistics
  • Proficiency in AI agent use, with the judgment to identify 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
  • Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls
  • Practical understanding of model systems (iPSC neurons, organoids, rodents, NHP, human cohorts)
  • Familiarity with core resources is a plus: Allen Brain Cell Atlas/BICAN, DANDI/NWB, OpenNeuro/BIDS, IBL, ADNI, PPMI, UK Biobank, ClinVar/gnomAD

Culture. We practice radical transparency: you’ll know how the company is doing, what’s working, and what isn’t. It’ll always be us against the problem, never each other. We’re opinionated but respectful, and we bring solutions with our problems. You decide how you work; we judge the output. We use AI constantly, so what we reward is original expert judgment, not AI output passed off as your own. You’ll start on the bench that fits your expertise and can move across teams as you build a track record. People who do well here and bring leadership experience can move quickly into senior roles. Outside of work, we have company outings most months, team off-sites, a Latch run club, cycling, boxing, ice skating, and soccer. Feel free to add to the list.

Compensation & Logistics

  • Contract: 1099 (or W-8BEN internationally), no end date
  • Pay: guaranteed for weeks 1-4 while you ramp, then paid per certified task. Most people in this position earn $120K–$180K+ (uncapped upside); certify twice the tasks/week, earn twice the pay that week.
  • Commitment: full-time, on your own schedule. Most of the team works 40+ hours a week.
  • Meetings: a few pod check-ins a week. The rest of your time is yours.
  • Location: remote (anywhere), hybrid, or onsite in SF. We prefer onsite.
  • Onsite perks: catered lunch and dinner daily, a waterfront office in Mission Bay, and monthly parking when available
  • Work authorization: US citizens, permanent residents, and OPT holders. We can’t support STEM OPT extensions or sponsorship.

Interview Process

We move fast: about 2–3 weeks from your first call with Latch to offer.

  • Intro Screen - Latch Talent Team
  • Take-Home Project - HackerRank
  • Technical Interview - Member of Technical Staff
  • Culture Interview - C-Suite
  • Offer

Source: LatchBio careers (Ashby)

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