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Research Scientist, Computational Pipelines

Cambridge, MA (on-site) · Full-time

The role

This is an engineering-oriented science role, owning and advancing the computational pipeline that turns terabyte-scale image volumes into reconstructions worth simulating. The job involves careful thinking about which changes matter and why, rigorous benchmarking, and sharp observation of where the pipeline fails in production, then fixing what you find.

You work, as needed, with other Mindspan teams (Scalable Chemistry, Optical Physiology, Microscopy and Optics, and Automation and Industrialization), and directly with the experimentalists and annotators whose data you train on, using logic and evidence to advance your work so as to boost the performance of all.

What you’ll do

  • Own the segmentation pipeline end to end: alignment, preprocessing, dense prediction, agglomeration, and handoff to proofreading.
  • Build the benchmarks: curated ground-truth volumes, and metrics that track what errors cost downstream.
  • Make evaluation automated and reproducible, with regression safeguards.
  • Run the data flywheel: find where the pipeline fails in production, request targeted annotations, and retrain.
  • Build the tooling that connects annotators and proofreaders to the training data.
  • Report measurable outcomes to institute leadership: throughput, cost, and error rates across conditions.
  • Documentation: keep pipeline documentation and experiment records that others can build on.

Required qualifications

  • Ph.D. in computer science, electrical engineering, applied mathematics, computational biology, neuroscience, or a related field, or equivalent industry experience.
  • Proven expertise training models for 3D and large-image segmentation on real, messy datasets.
  • Demonstrated ability to drive measurable improvements over many iterations, with rigorous benchmarking.
  • Strong Python and PyTorch, version control, and testing discipline.
  • Hands-on experience with chunked arrays, out-of-core processing, distributed computing, and cluster or cloud orchestration.
  • Sound engineering judgment, and the scientific rigor to tell real improvements from noise.
  • Ability to work directly with experimentalists and annotators.

Preferred qualifications

  • Experience with neural circuit reconstruction: affinity prediction, watershed, agglomeration, flood-filling, or synapse detection.
  • Familiarity with Neuroglancer, CAVE, webKnossos, VAST, or similar proofreading platforms.
  • Experience with production data engines or active learning, for example in autonomous driving or medical imaging.
  • Experience adapting large pretrained segmentation models to microscopy.
  • Experience with volume registration and alignment.
  • Contributions to open-source scientific software or benchmarks.

Culture we’re building

The disorders of the brain affect over 1,000,000,000 people around the world: Alzheimer’s, Parkinson’s, stroke, and other conditions. We operate with a sense of urgency, even as we look to understand the brain at its most fundamental levels.

We are hypercollaborative, and focused on impact over short-term markers of productivity. Creativity and failure are the stepping stones to scale, and working together with “strong opinions, weakly held” is our style.

We solve real engineering problems the best way we can: inventing fast when we have to, and using good existing solutions where they exist. We believe hard problems only yield to many disciplines working together, so collaboration is not optional.

We expect people to explore the unknown, which means making mistakes daily, owning them, and learning from them to improve and excel.

We are recruiting a team of scientists and engineers who exemplify all these values.

What we’re looking for

The ideal candidate is a scientist-engineer who naturally crosses disciplinary boundaries. You are intellectually curious, relentlessly practical, and happiest when solving problems that have never been solved before.

You have a strong detail orientation and exceptional organizational, planning, interpersonal, and communication skills. You are good at writing, can work independently and lead and manage, and can prioritize and multitask as needed. Self-motivation, commitment to high quality standards, and a service-oriented mindset are all key. You have good judgment, balancing flexibility and focus, action and planning, speed and thoughtfulness, as appropriate. You are open to giving and receiving feedback, constructively and thoughtfully, to advance scientific missions and personal growth.

This is an in-person job. Flexible hours may be required at times.

What we offer

The chance to build the segmenting pipeline of a new research institute alongside some of the most adventurous scientists in the field, with real autonomy and a direct line to the people setting the scientific agenda. You will get to contribute to addressing one of the most important unmet medical needs of our time, as part of the initial team. You will learn lots of things that probably cannot be learned any other way, as you solve problems, build, and work with others. As Mindspan grows, we expect this role to grow with it. We are excited to invest in someone who wants to take on increasing responsibility over time.

Comprehensive health, dental, vision, and family benefits, and a matching retirement contribution.

Competitive salary ($120,000 to $159,000), depending on experience.

Apply for this role →

Questions about the role go to jobs@mindspan.org.

The Mindspan Institute is an Equal Opportunity Employer. We are committed to a collaborative and scientifically rigorous environment for everyone who works here.

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