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Causal Inference Machine Learning Postdoctoral Jobs in Quincy, MA

Myana

Research Fellow - Deep Learning

Boston, MA · On-site

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 ...

Chewy

Machine Learning Engineer II

Boston, MA · On-site

$119K - $190K/yr

Ensure data quality and consistency for model training and inference. * Work with large datasets and apply data scaling techniques. * Select and build appropriate machine learning models based on ...

Cellarity

Machine Learning Scientist

Somerville, MA · On-site

... and/or causal representation methods, supporting downstream applications such as target ... Deploy and run inference on generative AI models using proprietary datasets on cloud platforms.

Cellarity

Machine Learning Scientist

Somerville, MA · On-site

... and/or causal representation methods, supporting downstream applications such as target ... Deploy and run inference on generative AI models using proprietary datasets on cloud platforms.

Engg

Machine Learning Scientist

Somerville, MA · On-site

... and/or causal representation methods, supporting downstream applications such as target ... Deploy and run inference on generative AI models using proprietary datasets on cloud platforms.

New

Tufts University

Postdoctoral Scholar

Medford, MA · On-site

$67K/yr

Overview Postdoctoral Scholar in Machine Learning for Physical Systems The Department of Electrical and Computer Engineering at Tufts University invites applications for a Postdoctoral Scholar in the ...

Manulife

Machine Learning Engineer

Boston, MA · Hybrid

$162K/yr

Develop and deploy backend services and microservices to support data ingestion, retrieval, and ML inference workflows; * Deploy, monitor, and maintain machine learning pipelines and backend services ...

Manulife

Machine Learning Engineer

Boston, MA · On-site

$162K/yr

Develop and deploy backend services and microservices to support data ingestion, retrieval, and ML inference workflows; * Deploy, monitor, and maintain machine learning pipelines and backend services ...

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Causal Inference Machine Learning Postdoctoral information

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$37.3K

$57K

$64.1K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Sep 15, 2026, the average yearly pay for causal inference machine learning postdoctoral in Quincy, MA is $57,013.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,300.00 and $59,400.00 per year, depending on experience, location, and employer.

What is a causal inference machine learning postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a causal inference machine learning postdoctoral researcher?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by causal inference machine learning postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

Is it difficult to get a causal inference machine learning postdoctoral position?

Securing a causal inference machine learning postdoctoral position can be competitive due to specialized skills required, such as expertise in statistical methods, programming (e.g., Python or R), and a strong research background. Candidates with relevant publications, strong recommendations, and experience in machine learning frameworks often have better chances, but the availability of such positions varies by institution and funding.

What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Quincy, MA look for?

The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Quincy, MA are:

What cities near Quincy, MA are hiring for Causal Inference Machine Learning Postdoctoral jobs?

Cities near Quincy, MA with the most Causal Inference Machine Learning Postdoctoral job openings:

Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Quincy, MA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 71% Full Time, 26% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $57,013 per year, or $27.4 per hour.

Research Fellow - Deep Learning

Boston, MA • On-site

Myana
See more jobs at Myanaexternal

Other

This job post has expired today. 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 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 will work at the intersection on the development, testing, and implementation 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
  • 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
Job Details

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.

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