Open Positions
We’re hiring. Join our interdisciplinary team at Stanford working at the intersection of systems neuroscience, neurotechnology, neuroscience theory, AI, mechanistic interpretability, and automated scientific discovery.
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We are seeking an Engineer Associate with strong mechanical engineering and mechatronic design skills to develop next generation robotic hardware and intracortical brain-interfacing technology. Our team is working to understand the neuroscience of intelligence, and mechatronic systems are critical to the depth and scale of our experimental ambitions. The ideal candidate will play an essential role in developing unique robotic systems that enable physical interactions within virtual environments. They will also prototype mechatronic microassembly processes that facilitate lightweight, highly scalable, precisely controlled neural interfaces, enabling the team to record neural activity and understand the brain at unprecedented scale.
This role is ideal for individuals who thrive at the rapidly evolving interface of neuroscience, engineering, software development, and artificial intelligence, and want to contribute to a uniquely interdisciplinary effort. This position is embedded within a vibrant team of neuroscientists, engineers, and software developers led by Andreas Tolias (toliaslab.org) and collaborators.
Please see the job posting for more information on role and responsibilities, qualifications, and how to apply. -
We are seeking a Data Engineer (Software Developer 2) to build and maintain the data platform supporting Enigma’s experimental workflows. You will partner with scientists and engineers to turn evolving experimental requirements into clear interfaces, observable pipelines, and dependable tools. You will develop reliable systems that move raw data from data acquisition systems through ETL/ELT transformation into downstream data and metadata stores. This role will involve data lakehouse and schema design and administration, data governance and observability, and performance optimization.
The ideal candidate enjoys owning systems end to end while working in a highly collaborative research environment.
Please see the job posting for more information on role and responsibilities, qualifications, and how to apply.
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We are seeking talented software developers/engineers to support the Enigma team by developing and scaling the systems that allow our scientists to iterate quickly. In this role, you will play a critical role in ensuring the reproducibility and production-readiness of our codebase, as well as implementing Continuous Integration and Continuous Deployment (CI/CD) processes for all teams involved in the project. Your work will be essential in maintaining the highest standards of software quality, reliability, and efficiency.
The ideal candidate enjoys owning systems end to end while working in a highly collaborative research environment.Please see the job posting for more information on role and responsibilities, qualifications, and how to apply.
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We are seeking talented postdoctoral researchers with an extensive background in experimental systems neuroscience and excellent quantitative skills. Ideal candidates will have several years of practical experience performing neuro-behavioral and/or neuro-physiological experiments, including visual stimulus design, eye tracking, MRI or large-scale electrophysiology techniques (ideally Neuropixels). Additionally, candidates should possess a strong background in quantitative fields such as Mathematics, Physics, Engineering, or Computer Science. This is a collaborative, cross-functional team, and project assignments will be tailored to match each postdoc’s strengths and growth goals. If you are passionate about building high-quality neuroscience experiments and data systems in a highly interdisciplinary environment, we encourage you to apply.
Role & Responsibilities:
Design and optimize large-scale electrophysiological and behavioral experiments using next generation custom-built hardware and software platforms
Develop and implement end-to-end experimental paradigms, including behavioral training and tracking, multi-Neuropixels recordings, imaging- and function-based recording path registration, and data quality control pipelines.
Collaborate closely with other teams in the Enigma Project to ensure efficient, scalable, and high-quality data collection and processing, with opportunities to explore scientific questions at the interface of neuroscience and AI in collaboration with theory and modeling teams.
Key Qualifications:
PhD in Neuroscience, Bioengineering, Electric Engineering, Computer Science, Physics, or a related field
Strong quantitative and analytical skills
Experience in either experimental neuroscience (e.g., in vivo neurophysiological recordings, behavioral training) or computational data analysis (e.g., spike sorting, neural signal processing)
Excellent communication and collaborative skills
A strong sense of curiosity and initiative, and a desire to collaboratively reimagine and reinvent traditional systems neuroscience methodologies
Preferred Qualifications:
Hands-on experience with Neuropixels or other large-scale electrophysiological recordings
Experience designing, prototyping, and/or optimizing innovative experimental systems
Strong background and extensive knowledge in visual neuroscience, including anatomy, physiology, and modeling of visual systems
Background in developing visual, motor, or cognitive behavioral tasks and training animals
Experience implementing and optimizing eye tracking, body tracking, and/or visual reality environments
Proficiency in Python and scientific computing libraries
Familiarity with spike sorting workflows (e.g., Kilosort, SpikeInterface) and neural data quality control
Experience with imaging data processing, anatomical or functional registration, and 3D planning/reconstruction for recording trajectories
What We Offer:
A collaborative, interdisciplinary research environment spanning neuroscience, artificial intelligence, and systems engineering
Opportunities to work with cutting-edge tools and contribute to high-impact neuroscience infrastructure
Flexibility in project focus and opportunities to lead or co-lead initiatives based on your expertise
Competitive salary and benefits
Strong mentoring and career development support
Application: Please send your CV and a one-page statement of interest to: recruiting@enigmaproject.ai
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The Enigma Project is seeking a Research Scientist in Computational Neuroscience to turn large-scale neural recordings and brain foundation models into scientific discovery. The successful candidate will join a team of neuroscientists, machine learning researchers, and engineers working together on a small number of high-impact flagship projects, rather than building an independent research line. Scientific questions are developed and pursued collectively, and the work is supported by dedicated engineering and infrastructure teams that build and run the analysis pipelines, models, and tooling the science depends on.
The role will suit someone excited by the prospect of doing scientific discovery at an unprecedented scale, in an environment that combines academic excellence with industry-scale resources and execution. The emphasis is on generating and prioritizing the questions worth asking of an unusually rich combination of data and models, on judging what those data and models can currently answer, and on driving flagship projects through to results that change how the field understands neural computation. Credit and authorship are shared and reflect contributions to collective, team-based projects.
Role & Responsibilities:
Generate and prioritize scientific questions about neural representation and computation that can be addressed with large-scale neural recordings and brain foundation models, and develop them into concrete, testable hypotheses.
Contribute to a small number of shared, high-impact flagship projects as part of a team of neuroscientists, machine learning researchers, and engineers.
Design and run in-silico experiments on brain foundation models to explore model behavior, characterize neural tuning and population structure, and generate predictions about the biological system.
Analyze large-scale neural activity and behavioral data using statistical, machine learning, and population-geometry methods, and evaluate model predictions against experimental data.
Work with the experimental team to identify, prioritize, and design validation experiments, including model-guided and closed-loop paradigms.
Define the analysis, modeling, and tooling requirements of the scientific program for the engineering team, and work closely with engineers to run analyses at a scale no individual researcher could reach alone.
Work with agentic AI tools and AI scientists to automate analyses and scale hypothesis generation and evaluation.
Interpret findings in the context of the wider systems and computational neuroscience literature, and assess their scientific significance and limitations.
Communicate results through team publications, conference presentations, and internal scientific meetings.
Contribute to the scientific direction of the project and share scientific expertise across the team.
Key Qualifications:
Ph.D. in Neuroscience, Computational Neuroscience, Biology, Physics, Computer Science, or a related field.
Two or more years of research experience beyond the Ph.D., for example postdoctoral training, in systems, computational, or experimental neuroscience.
Deep understanding of visual neuroscience, including the anatomy, physiology, and computational principles of the visual system, and command of the relevant primary literature.
Direct experience with physiological or behavioral experiments, either hands-on or through sustained close collaboration with the experimentalists generating the data.
Demonstrated experience analyzing large-scale neural or behavioral datasets, such as two-photon calcium imaging, high-density electrophysiology, or high-throughput behavioral recordings.
Fluency in Python and its scientific computing ecosystem, and in the machine learning methods used to analyze neural data, including practical experience with a deep learning framework such as PyTorch.
Strong publication record in neuroscience, demonstrating scientific depth and the ability to carry projects through to completion.
Demonstrated ability to formulate research questions independently, design analyses or experiments to address them, and carry projects through to publication.
Enthusiasm for team-based science, and a demonstrated ability to work productively on shared projects with scientists and engineers from other disciplines.
Excellent written and verbal communication skills.
Preferred Qualifications:
Research experience with non-human primates.
Experience working with encoding models or digital twin models of neural activity, and with model-guided or closed-loop experimental design.
Hands-on experience with in vivo neurophysiology, for example two-photon imaging or Neuropixels recordings.
Experience working with agentic systems for automating scientific analysis.
Experience working within large, collaborative, multi-investigator research programs.
Experience specifying technical requirements to, or working alongside, dedicated engineering or data infrastructure support.
Contributions to open-source scientific software.
What We Offer:
The opportunity to contribute to fundamental research on the principles underlying perception, cognition, and natural intelligence.
Access to neural datasets collected at a scale and resolution that are difficult to obtain anywhere else, together with digital twins and foundation models built from these data.
The opportunity to develop computational methods and agentic tools that enable new forms of analysis and in-silico experimentation at scale.
Close collaboration with neuroscientists, machine-learning researchers, neurotechnologists, and engineers working toward a shared scientific mission.
An ambitious, collaborative research environment that combines the intellectual freedom of academia with the coordination and shared infrastructure needed to conduct science at scale.
Opportunities to contribute to scientific publications, open-source tools, and broadly used research resources.
Mentorship and support for growth as both a technical contributor and a scientific collaborator.
Competitive Stanford salary and benefits and access to Stanford’s broader research community.
Application:
Please send your CV and a one-page statement of interest to: recruiting@enigmaproject.ai
For all hiring inquiries: recruiting@enigmaproject.ai.