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Associate Data Scientist Deep Learning Jobs in Massachusetts

... data science * Experience building neural networks using standard deep learning tools (e.g., PyTorch, JAX, TensorFlow), including implementing new layers/network architectures, model training ...

$64K - $65K/yr

The Data, AI and Genome Sciences (DAGS) department seeks a talented computational biologist to join ... Expertise applying deep learning approaches to image based phenotypic profiling and cell ...

Data Scientist

Cambridge, MA · On-site +1

$121K - $194K/yr

ModernaTX, Inc. seeks a Data Scientist for its Cambridge, Massachusetts location. Here's What You ... Deep learning models including PyTorch. * May telecommute up to 30% of the time. The salary range ...

Data Scientist

Cambridge, MA · On-site

$121K - $194K/yr

ModernaTX, Inc. seeks a Data Scientist for its Cambridge, Massachusetts location. Here's What You ... Deep learning models including PyTorch. * May telecommute up to 30% of the time. The salary range ...

Showing results 41-60

Associate Data Scientist Deep Learning information

What is the difference between Associate Data Scientist Deep Learning vs Data Scientist?

AspectAssociate Data Scientist Deep LearningData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related; familiarity with deep learning frameworksBachelor's or Master's in CS, Statistics, or related; broader data analysis skills
Work EnvironmentFocus on developing deep learning models, often in AI or ML teamsBroader data analysis, visualization, and modeling across various projects
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, retail, tech, and more

The main difference is that Associate Data Scientist Deep Learning specializes in developing deep learning models, requiring specific knowledge of neural networks and frameworks. Data Scientists have a broader scope, including traditional data analysis, statistical modeling, and visualization. Both roles often require similar educational backgrounds but differ in technical focus and project types.

What are the most commonly searched types of Data Scientist Deep Learning jobs in Massachusetts? The most popular types of Data Scientist Deep Learning jobs in Massachusetts are:

$70K - $71K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.


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 developedDystoniaNet platformand 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 developedDystoniaNet platformand 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).

Responsibilitiesinclude 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.