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Causal Inference Machine Learning Postdoctoral Jobs in Cambridge, 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

See Cambridge, MA salary details

$38.8K

$59.3K

$66.7K

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 Cambridge, MA is $59,265.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,500.00 and $61,800.00 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 are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Cambridge, MA?

For Causal Inference Machine Learning Postdoctoral jobs in Cambridge, MA, the most frequently searched job titles are:

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

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

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

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

Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Cambridge, MA as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $59,265 per year, or $28.5 per hour.

Postdoctoral Fellowships in Networking Support for Machine Learning

Cambridge, MA • On-site

Harvard University
Colleges, Universities, and Professional Schools • 51 - 200 employees
Learn more about Harvard Universityexternal

$67K - $91K/yr

Full-time

Re-posted 29 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

Job description

Position
Details
Title
Postdoctoral Fellowships in Networking Support for Machine Learning
School
Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area
Computer Science
Position Description
The John A. Paulson School of Engineering and Applied Sciences at Harvard University (SEAS) seeks applicants for a postdoctoral position in networking support for machine learning systems. The initial term for this position is one year; reappointment for a second year is contingent upon funding.
The postdoc will work with closely with Minlan Yu and other group members focused on networking support for machine learning systems, as well as possibly other Harvard faculty.
The candidate will be expected to publish scholarly papers, attend internal, domestic, and international conferences and meetings, and take on a mentorship role for undergraduate and graduate students.
Basic Qualifications
Candidates are required to have a doctorate or terminal degree in Computer Science or a related area by the expected start date.
Additional Qualifications
Special Instructions
Contact Information
Gioia Sweetland
Contact Email
gioia@seas.harvard.edu
Salary Range
$67,600 - $91,826
Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.
Minimum Number of References Required
3
Maximum Number of References Allowed
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