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Machine Learning Neuroscience Jobs in Massachusetts

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Machine Learning Neuroscience information

What are the key skills and qualifications needed to thrive in the machine learning neuroscience position, and why are they important?

To thrive in a Machine Learning Neuroscience role, you need a solid background in neuroscience, advanced machine learning methods, statistical analysis, and preferably a graduate degree in a related field. Experience using programming languages such as Python or MATLAB, along with tools like TensorFlow, PyTorch, and neuroimaging platforms, is highly desirable. Strong analytical thinking, effective communication, and the ability to work collaboratively across interdisciplinary teams are vital soft skills. These competencies enable professionals to develop impactful models, interpret complex brain data, and drive innovative research or clinical applications in neuroscience.

What is a machine learning neuroscience?

A Machine Learning Neuroscience job involves using machine learning techniques to analyze and model neural data, helping to understand brain function or improve neurotechnology. Professionals in this field work at the intersection of artificial intelligence, neuroscience, and data science, often developing algorithms to interpret neural signals or enhance brain-computer interfaces. Roles can be found in academia, healthcare, and tech industries, contributing to research, diagnosis, or neuroadaptive systems. Strong skills in programming, statistics, and neuroscience fundamentals are typically required.

What are the typical daily tasks and team dynamics for someone working in a machine learning neuroscience role?

In a Machine Learning Neuroscience position, your daily activities might include designing and running algorithms on neurological datasets, interpreting results, refining models, and collaborating with neuroscientists and clinicians. You’ll often work closely with cross-functional teams, contributing technical expertise to research studies or healthcare projects. Regular team meetings, data discussions, and collaborative problem-solving are a central part of the work environment. This collaborative structure fosters innovative ideas and ensures that machine learning approaches are well-suited to real-world neuroscience challenges.

Is machine learning used in neuroscience?

Machine learning neuroscience involves applying machine learning techniques to analyze neural data, model brain functions, and develop brain-computer interfaces. Professionals in this field often use tools like Python, TensorFlow, and neural imaging data to advance understanding of the brain. It is a growing area that combines expertise in both neuroscience and machine learning algorithms.
What are popular job titles related to Machine Learning Neuroscience jobs in Massachusetts? For Machine Learning Neuroscience jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Machine Learning Neuroscience jobs in Massachusetts look for? The top searched job categories for Machine Learning Neuroscience jobs in Massachusetts are:
Machine Learning Neuroscience jobs near you
Infographic showing various Machine Learning Neuroscience job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Tech Staff Neurocognitive Analysis, Modeling, and Simulation

MIT Lincoln Laboratory

Lexington, MA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 29 days ago

Job description

The Human Health & Performance Systems Group develops human-centered technologies to overcome operational challenges and to enhance human capability in domains of interest to national security. Our research programs focus on innovative and objective solutions in the areas of integrated wearable systems, human-machine teaming, enhanced communications, neurocognitive analytics, and medical technologies. Our group is highly interdisciplinary and includes scientific experts in physiology, cognitive science, neuroscience, psychology, biomechanics, computer science, engineering, and physics. Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.
Job Description
The Human Health & Performance Systems Group is searching for a candidate to participate in and lead projects related to detecting, monitoring, and rehabilitating psychological, neurological and sensory (e.g., auditory, visual, vestibular) disorders, neurotrauma, and cognitive overload and fatigue. Analysis involves features based on mechanistic neuro-biophysical and neuro-motor computational modeling, neuromorphic (software and hardware) simulations, neural interface (e.g., EEG) technology, and machine learning coupled to brain imaging and neural tracing representations. We seek nonintrusive interactive interfaces to maximize effect of treatment and training and maximize resilience. Interfaces can take the form of neural and physiological wearables, sensory feedback therapies, and virtual humans and environments.
The candidate will assist in developing neural-science-based algorithms, brain and human computer interfaces, and computational models, as well as data collection and analysis. As experience is gained, the candidate will be required to generate their own innovative ideas and seek support for these program ideas. Background is required in advanced signal processing and machine learning. Background is desired in neuroscience (preferably modeling of neuro-motor and sensory systems and the neural basis of speech perception and production and vision). It is also desirable that the candidate have skills in neuromorphic computing (software and hardware) at both neural system and neural cell levels for real-time neurocomputational simulations. Hardware development experience is desirable. Candidate should also demonstrate abilities that include programming with Python, and/or C++, as well as statistical analysis and machine learning (scikit-learn, PyTorch, Tensorflow) capabilities. The candidate should hold a Ph.D. or Sci.D. in Biomedical Engineering, Electrical Engineering, Mechanical Engineering, Computer Science, Neurocognitive Science, Speech/Hearing Sciences, or a similar technical field.
Recent Graduate Hiring Range: $145,200 - $170,000
Experienced Hiring Range: $145,200 - $220,000
Disclaimer: MIT Lincoln Laboratory provides a typical hiring range as a good faith estimate of what we reasonably expect to offer for this position at the time of posting. The final salary offered to a selected candidate will depend on various factors, including-but not limited to-the scope and responsibilities of the role, the candidate's experience, skills and education/training, internal equity considerations and applicable legal requirements. This range reflects base salary only and does not include additional forms of compensation or benefits.
At MIT Lincoln Laboratory, our exceptional career opportunities include many outstanding benefits to help you stay healthy, feel supported, and enjoy a fulfilling work-life balance. Benefits offered to employees include:
  • Comprehensive health, dental, and vision plans
  • MIT-funded pension
  • Matching 401K
  • Paid leave (including vacation, sick, parental, military, etc.)
  • Tuition reimbursement and continuing education programs
  • Mentorship programs
  • A range of work-life balance options
  • ... and much more!

Please visit our Benefits page for more information. As an employee of MIT, you can also take advantage of other voluntary benefits, discounts and perks.
Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.
MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.
Requisition ID: 42798

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