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Internship Computer Science Postdoc Jobs in Boston, MA

NorthEastern

Postdoctoral Research Fellow

Boston, MA · On-site +1

The Postdoctoral Researcher will be based out of either the Boston, MA or Portland, ME campus and ... D. in computer science, AI, Data Science, computational biology, Ethics in AI, or health-related ...

Massgeneralbrigham

Postdoctoral Fellow

Belmont, MA · On-site

$54K - $73K/yr

... and computer science skills oPossess exceptional written and oral communication skills as ... Assistance in guiding research technicians, graduate students, interns, and other trainees in the ...

McLean Hospital

Postdoctoral Fellow

Belmont, MA · On-site

$54K - $73K/yr

... and computer science skills o Possess exceptional written and oral communication skills as ... Assistance in guiding research technicians, graduate students, interns, and other trainees in the ...

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What is the difference between Internship Computer Science Postdoc vs Research Scientist?

AspectInternship Computer Science PostdocResearch Scientist
Required credentialsTypically PhD or nearing completion in Computer SciencePhD in Computer Science or related field
Work environmentAcademic labs, universities, research institutionsResearch labs, industry R&D departments, universities
Employer and industry usagePrimarily academic and research institutionsIndustry companies, government agencies, academia
Common search and comparison intentUnderstanding early career research rolesExploring advanced research positions in industry or academia

Internship Computer Science Postdocs are typically short-term research positions for PhD candidates or recent graduates, mainly in academic settings. Research Scientists usually hold PhDs and work in industry or research labs, focusing on applied or fundamental research. While both roles involve research, internships are entry-level and temporary, whereas Research Scientists are more permanent and senior roles.

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Postdoctoral Research Position in Causal Inference

Postdoctoral Research Position in Causal Inference

Harvard University

Cambridge, MA • On-site

$75K/yr

Full-time

Re-posted 2 days ago

Harvard University rating

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Company rating: 8.4 out of 10

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Job description

Position
Details
Title
Postdoctoral Research Position in Causal Inference
School
Harvard T.H. Chan School of Public Health
Department/Area
Biostatistics
Position Description
We invite applications for a full-time Postdoctoral Research Fellow to join the causal inference team supervised by Professor Francesca Dominici. The position will focus on developing and applying novel causal inference methods for large-scale observational studies, with a particular emphasis on environmental exposures and public health. Core data resources include nationwide claims, linked with rich contextual information such as census data, weather records, and high-resolution air pollution and related environmental exposures data.
Motivated by relevant public health and policy questions, the goal is to develop methodologies for the identification, estimation, transportability, and generalization of the causal effects in complex real-world settings. Among others, methodological areas will span:
• Causal inference for spatiotemporal data,
• Methods for heterogeneous treatment effects estimation,
• Methods for multiple exposures, multiple outcomes,
• ML and AI methods for causal inference,
• Bayesian causal inference,
• methods for transportability and generalizability of causal effects across space, time, and populations.
Duties and Responsibilities
• Design, develop and implement novel causal inference methods in the areas listed in the position description.
• Work with large, high-dimensional datasets.
• Lead and contribute to manuscripts for high-impact journals (e.g., top Statistics journals and Nature-like journals).
• Present findings in internal meetings and at national/international conferences.
• Collaborate with an interdisciplinary team (bio)statisticians, data scientists, computer scientists, and climate scientists.
• Contribute to open-source code and reproducible pipelines.
Basic Qualifications
• PhD (completed or near completion) in Statistics, Biostatistics, Data Science, Computer Science or a closely related field.
• Demonstrated expertise in causal inference, with interest in methods development.
• Experience with statistical and ML methods, including at least one of the following: Bayesian methods, deep learning, spatiotemporal modeling, high-dimensional statistics.
• Proficiency in statistical programming (R and/or Python) and good practices for reproducible research.
• Experience working with large datasets and cloud computing environments.
• Excellent written and oral communication skills, with a track record of peer-reviewed publications commensurate with career stage.
• Ability to work in a collaborative, interdisciplinary environment.
Additional Qualifications
Prior experience with one or more of:
• Health claims data, EHRs, or other large-scale health/administrative datasets.
• Environmental, climate, or air pollution exposure data.
Familiarity with LLMs.
Special Instructions
Please submit the following materials:
• Cover letter describing your research interests, relevant experience, and fit for this position.
• Curriculum vitae including a list of publications.
• One to three representative publications or preprints.
Names and contact information for 2-3 references.
Contact Information
Catherine Adcock
Contact Email
catherine_adcock@harvard.edu
Salary Range
$75,000
Minimum Number of References Required
2
Maximum Number of References Allowed
3
Keywords
Causal inference; spatiotemporal modeling; generalizability; transportability; environmental health

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