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Summer Causal Inference Jobs in Massachusetts (NOW HIRING)

Stryker

$35/hr

Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis * Experience with NLP applied to unstructured healthcare text * Prior coursework ...

New

Stryker

$35/hr

Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis * Experience with NLP applied to unstructured healthcare text * Prior coursework ...

New

Stryker

$35/hr

Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis * Experience with NLP applied to unstructured healthcare text * Prior coursework ...

New

Stryker

$35/hr

Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis * Experience with NLP applied to unstructured healthcare text * Prior coursework ...

New

Stryker

$35/hr

Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis * Experience with NLP applied to unstructured healthcare text * Prior coursework ...

New

Stryker

$35/hr

Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis * Experience with NLP applied to unstructured healthcare text * Prior coursework ...

New

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Summer Causal Inference information

What is a summer causal inference?

A Summer Causal Inference position is typically a short-term research or internship role focused on applying statistical methods to determine causal relationships between variables, often in fields like economics, public policy, or data science. Individuals in this position work on projects that require designing experiments or analyzing observational data to infer causality rather than just correlation. The role is ideal for students or early-career professionals seeking hands-on experience in causal inference techniques during the summer months.

What types of projects and methodologies can I expect to work on as a summer causal inference intern?

As a Summer Causal Inference intern, you'll typically work on projects involving the design and analysis of experiments or observational studies to determine cause-and-effect relationships. You may use methodologies such as propensity score matching, difference-in-differences, instrumental variables, or regression discontinuity designs. Collaboration with data scientists, economists, and business stakeholders is common, as you'll help translate findings into actionable insights. Expect to handle real-world datasets and communicate your results through presentations or reports, gaining valuable experience in both technical and applied aspects of causal inference.

What are the key skills and qualifications needed to thrive as a summer causal inference researcher, and why are they important?

To thrive as a Summer Causal Inference Researcher, you need a solid background in statistics, econometrics, and data analysis, typically supported by coursework or a degree in a quantitative field. Familiarity with statistical programming languages like R or Python and experience using tools such as STATA or MATLAB are often required. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are valuable soft skills. These skills and qualities are crucial for accurately identifying causal relationships in data and effectively collaborating within interdisciplinary research teams.

What are the most commonly searched types of Causal Inference jobs in Massachusetts?

The most popular types of Causal Inference jobs in Massachusetts are:

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For Summer Causal Inference jobs in Massachusetts, the most frequently searched job titles are:

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Summer Causal Inference jobs near you

Postdoctoral Associate

Massachusetts Institute of Technology

Cambridge, MA • On-site

Full-time

Re-posted 24 days ago

Massachusetts Institute Of Technology rating

8.8

Company rating: 8.8 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

47th of 630 rated colleges and universities

Job description

Description
The MIT Sloan School of Management and Social and Ethical Responsibilities of Computing (SERC) in the Schwarzman School of Computing jointly seek to hire a Postdoctoral Associate, beginning in Summer 2025 to lead collaborative projects on generative AI and reasoning,
The appointment is for one year starting Summer 2025 (flexible start date), with the possibility of renewal for a second year. The Postdoctoral Associate should expect to work from Cambridge, MA for the duration of the appointment, with some potential for travel. The position is eligible for MIT benefits.
The selected candidate will provide supervision and guidance to students, and researchers while engaging in activities that support the general mission of MIT Sloan and SERC. The Postdoctoral Associate will also collaborate with other post docs, SERC scholars, and instructors.
About Social and Ethical Responsibilities of Computing (SERC)
The Social and Ethical Responsibilities of Computing (SERC) is facilitating the development of responsible "habits of mind and action" for those who create and deploy computing technologies and foster the creation of technologies in the public interest. Through a teaching, research and engagement framework, SERC is working to train students, encourage research to assess the broad challenges and opportunities associated with computing, and improve design, policy, implementation, and impacts. For more details about this cross-cutting program, please see our website.
Principal Duties and Responsibilities:
The postdoc's time will be allotted as such:
o 50% towards ongoing and new applied research projects under the supervision of Professors Sertac Karaman and Eric So;
o Approximately 25% of time allotted for independent research.
o Approximately 20 of time allotted for participating in SERC's community-building activities and programming, including to lead a SERC Scholar Group throughout the academic year.
o Additional responsibilities as determined by organizational needs.
Supervision Received:
The position works closely with Professors Sertac Karaman and Eric So. Position requires ability to perform with minimal supervision.
Supervision Exercised:
No direct reports. May monitor the academic work of research associates and graduate research assistants involved in specific projects.
Qualifications
1. A Ph.D. in Computer Science or other related field required.
2. Advanced quantitative methods training with expertise in experiments, identification, and causal inference required. Qualitative fieldwork experience is also preferred.
3. Proven record of academic excellence, research achievement and publication that contributes to the study of the above areas.
4. Attention to detail; self-motivation and ability to work on projects independently; proven ability to handle multiple projects concurrently and meet deadlines.
5. Demonstrated proficiency in Python and willingness to contribute to open-source.
Application Instructions
Please provide the following as compiled in one attachment:
1. Cover letter
2. CV
3. Research statement of primary research interests including ongoing and planned projects (3-5 pages)
Shortlisted candidates will be asked to provide three letters of reference.
Priority review will be given to application materials submitted through careers.mit.edu.

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