Research Scientist, Deep Learning Models

Mindspan Institute; Cambridge (MA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Retirement matching

Job summary

Mindspan Institute in Cambridge, MA is seeking a hands-on deep learning scientist/engineer to design, train, and evaluate models that turn large microscopy volumes into actionable data, including segmentation, tile stitching, and downstream detection/classification.

You will report to the Head of Computation and collaborate across Microscopy and Optics, Expansion Microscopy, Scalable Chemistry, and Automation teams.

Qualifications

• Advanced degree or equivalent industry experience in computer science, electrical engineering, applied mathematics, physics, computational biology or neuroscience, or a related field.
• Direct hands-on experience designing and training deep learning models.
• Demonstrated experience with image segmentation or dense prediction on 3D or large 2D image data.
• Strong software engineering: Python, version control, testing, and code that other people can run and extend.
• Experience training on multi-GPU systems or a compute cluster.
• Excellent engineering judgment and scientific rigor, including the discipline to tell a real improvement from noise.

Responsibilities

• Design, train, and evaluate deep learning models for microscopy data.
• Tackle segmentation, stitching/alignment of image tiles, and downstream detection/classification.
• Collaborate with the Head of Computation and cross-team groups to advance methods.
• Document methods and results, and iteratively improve models based on evidence.

Skills

Deep learning

Python

Image segmentation

Multi-GPU training

Scientific rigor

Education

PhD in a relevant field or equivalent industry experience

Tools

PyTorch

Git

Job description

This is a hands‑on modeling role. You will design, train, and evaluate the deep learning models that turn large microscopy volumes into usable data: segmentation, the stitching and alignment of image tiles and sections, and the detection and classification models that follow. The job will heavily depend on expertise and fluency in DL frameworks like PyTorch: reading the literature, choosing an architecture that fits the data, training it at scale, and finding out where and why it fails.

You report to the Head of Computation, and work, as needed, with other Mindspan teams (Microscopy and Optics, Expansion Microscopy, Scalable Chemistry, and Automation and Industrialization), using logic and evidence to advance your work so as to boost the performance of all.

The position is intended for a generalist: someone who is as comfortable adapting a pretrained vision model as writing a new loss function, and who picks the model to fit the problem rather than the reverse. Given the multidisciplinary nature of the job, it is ideal for a person who enjoys problem solving across intellectual boundaries, at the level of concepts as well as of hands‑on debugging. It also requires systematic documentation, analysis, and iterative problem solving, to arrive at working models, apply them, and share them.

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 required, 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.

Required Qualifications

• Advanced degree or equivalent industry experience in computer science, electrical engineering, applied mathematics, physics, computational biology or neuroscience, or a related field.
• Direct hands‑on experience designing and training deep learning models.
• Demonstrated experience with image segmentation or dense prediction on 3D or large 2D image data.
• Strong software engineering: Python, version control, testing, and code that other people can run and extend.
• Experience training on multi‑GPU systems or a compute cluster.
• Excellent engineering judgment and scientific rigor, including the discipline to tell a real improvement from noise.

Preferred Qualifications

• Experience with image registration, stitching, or alignment of large tiled or serial‑section datasets.
• Experience with connectomics or other biological microscopy data (electron, light, or expansion microscopy).
• Experience with self‑supervised learning, or with adapting large pretrained vision models to a new domain.
• Experience with chunked array formats (Zarr, N5, precomputed) and data too large for one machine.
• Publications, open‑source models, or results on public benchmarks.

The ideal candidate is a scientist‑engineer who can read a paper on Monday and have a working reimplementation by Friday. You are intellectually curious, relentlessly practical, and happiest when solving problems that have never been solved before. You choose methods by what the data needs, and you can explain why a model works as well as why one fails.

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.

The chance to build the core models 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 ($180,000 to $260,000), depending on experience.