1

Temporary Machine Learning Postdoc Jobs in Taunton, MA

This postdoctoral position will involve leading independent research, as well as conducting ... machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities ...

About the Opportunity Conduct research on machine learning, control theory, and synthetic biology ... The Postdoctoral Associate will give presentations of their work, will help write papers reporting ...

... machine learning Data harmonization and integration * Record of research productivity evidenced by peer-reviewed publications, open-source software, or other scholarly outputs * Excellent written and ...

next page

Showing results 1-20

Temporary Machine Learning Postdoc information

What is a temporary machine learning postdoc?

A Temporary Machine Learning Postdoc is a fixed-term research position, typically held at a university or research institution, focused on advancing knowledge and techniques in machine learning. Postdoctoral researchers in this role work on specific projects, often collaborating with faculty, graduate students, or industry partners. The position is designed to provide advanced training and research experience after earning a PhD, usually lasting from several months to a couple of years. Temporary postdocs may contribute to publishing academic papers, developing algorithms, and mentoring students, while preparing for longer-term academic or industry careers.

What skills and qualifications are needed to thrive as a temporary machine learning postdoc?

To thrive as a Temporary Machine Learning Postdoc, you need a PhD in a relevant field, a solid grasp of machine learning theory, and strong programming skills (often in Python or R). Experience with tools such as TensorFlow, PyTorch, and high-performance computing environments, as well as a record of peer-reviewed research, is typically required. Strong analytical thinking, collaboration, and effective communication help you stand out in this research-intensive role. These skills are essential for advancing cutting-edge research, publishing impactful findings, and contributing to interdisciplinary projects.

What types of projects and collaborations can a temporary machine learning postdoc expect to engage in?

A Temporary Machine Learning Postdoc typically works on cutting-edge research projects, often contributing to ongoing studies or initiating novel investigations within the field. Collaboration is common, both within their immediate research group and with interdisciplinary teams, such as data scientists, domain experts, or industry partners. Postdocs may also mentor graduate students, present findings at conferences, and publish papers, gaining valuable experience that can lead to academic or industry roles. The environment is fast-paced and research-driven, offering opportunities for professional growth and expanding one's research portfolio.

What is the difference between Temporary Machine Learning Postdoc vs Data Scientist?

AspectTemporary Machine Learning PostdocData Scientist
CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often requires experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research centersBusiness, technology, finance, healthcare
Search & Comparison IntentUnderstanding research-focused roles, academic opportunitiesIndustry roles, applied data analysis, business impact

The Temporary Machine Learning Postdoc is primarily research-oriented, often in academic or research settings, requiring a PhD. In contrast, a Data Scientist typically works in industry, applying data analysis and machine learning to solve business problems, often with a Bachelor's or Master's degree. Both roles involve machine learning skills but differ in environment, focus, and experience level.

What are the most commonly searched types of Machine Learning Postdoc jobs in Taunton, MA?

The most popular types of Machine Learning Postdoc jobs in Taunton, MA are:

Infographic showing various Temporary Machine Learning Postdoc job openings in Taunton, MA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Research Fellow - Deep Learning

Boston, MA • On-site

$70K - $71K/yr

Full-time

Re-posted 27 days ago


Brigham and Women's Hospital rating

8.1

Company rating: 8.1 out of 10

Based on 101 frontline employees who took The Breakroom Quiz

119th of 1,066 rated hospitals


Job description

Site: Massachusetts Eye and Ear Infirmary
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
Job Summary
We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes. This work will be directly related to the extension of our recently developed DystoniaNet platform and will include brain MRI datasets from patients with dystonia, other movement disorders, and healthy individuals.
The postdoctoral fellow will be part of a multidisciplinary team of neuroscientists, neurologists, laryngologists, and geneticists at Mass Eye and Ear and Mass General Hospital and work at the intersection on the development, testing and implement of DystoniaNet in the clinical setting. This position is best suited for an individual with a broad computer science background interested in understanding and examining critical clinical problems and developing research solutions for their translation to healthcare. The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech).
Qualifications
Postdoctoral Fellow in Deep Learning
We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes. This work will be directly related to the extension of our recently developed DystoniaNet platform and will include brain MRI datasets from patients with dystonia, other movement disorders, and healthy individuals.
The postdoctoral fellow will be part of a multidisciplinary team of neuroscientists, neurologists, laryngologists, and geneticists at Mass Eye and Ear and Mass General Hospital and work at the intersection on the development, testing and implement of DystoniaNet in the clinical setting. This position is best suited for an individual with a broad computer science background interested in understanding and examining critical clinical problems and developing research solutions for their translation to healthcare. The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech).
Responsibilities include but may not be limited to
  • Experimental data collection and processing
  • Development and refinement of deep learning and other benchmark algorithms for predictive classification of dystonia and other related disorders
  • Clinical translation and implementation of the developed algorithms and interactions with clinicians for their testing
  • Establishment of new and fostering of existing collaborations
  • Participation in the regulatory aspects of clinical translation and patenting
  • Presentation of the results at the scientific meetings and publication of journal articles
  • Mentoring junior staff

Qualifications and Skills
  • PhD or an equivalent degree in computer science, neuroscience, biomedical engineering, or related fields
  • Broad proficiency and experience with supervised and unsupervised machine-learning methods, expertise in building neural network architectures
  • Experience with neuroimaging data processing
  • Advanced programming skills (Python and/or Matlab), including deep learning packages (e.g., TensorFlow or Keras)
  • Knowledge and experience with cloud-based computational platforms (e.g., AWS)
  • Excellent verbal and written communication skills
  • Strong publication record and academic credentials
  • Ability to work effectively both independently and in collaboration with multiple investigators

Pay Range: $70,000.00 - $71,750.00/Annual
Additional Job Details (if applicable)
Remote Type
Onsite
Work Location
243-245 Charles Street
Scheduled Weekly Hours
40
Employee Type
Regular
Work Shift
Day (United States of America)
EEO Statement:
5110 Massachusetts Eye and Ear Infirmary is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran's Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership "looks like" by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.

What Brigham and Women's Hospital employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom