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Arvind Satyanarayan

Top university

7 months ago

Postdoctoral Position in Human-AI Interaction, HCI, and Reinforcement Learning at MIT Massachusetts Institute of Technology in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

The position is a paid postdoctoral appointment at MIT, initially for one year starting September 2026, with the possibility of renewal for a second year. No specific stipend or salary amount is mentioned.

Deadline

Expired

Country flag

Country

United States

University

Massachusetts Institute of Technology

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Keywords

Computer Science
Anthropology
Sociology
Information Technology
Reinforcement Learning
Hci
Large Language Models

About this position

The Massachusetts Institute of Technology (MIT) is seeking a postdoctoral researcher in Human-AI Interaction, with a focus on reinforcement learning and ethnographic rewards. The position is part of a research effort to develop AI agents that promote human metacognition and sociality, using reinforcement learning with ethnographic rewards (RLER). This involves combining multi-turn RL with the observation of workplace skill development to derive reward functions for complex behaviors, such as knowing when to step back or prompting reasoning articulation.

The successful candidate will work on designing novel interfaces, including productive friction, contrastive explanations, and thought-trace visualizations, and will collaborate with an interdisciplinary team spanning HCI, machine learning, anthropology, and sociology. The postdoc will work closely with Professors Arvind Satyanarayan, Mitchell L. Gordon, Zana Buçinca, Susan Silbey, and Graham Jones, and will be part of MIT's Social and Ethical Responsibilities of Computing (SERC) program.

Applicants must hold a PhD in Computer Science or a closely related field, with hands-on experience in training or fine-tuning large language models. Candidates with interests in multi-turn RL, human-AI interaction, or AI alignment are strongly encouraged to apply. The position requires the ability to advance research independently and a willingness to engage in interdisciplinary collaboration.

The initial appointment is for one year, starting September 2026, with the possibility of renewal for a second year. Applications are considered on a rolling basis until May 1, 2026, and early applications are strongly preferred. For more information and to apply, please see the provided Google Form link. This is a paid postdoctoral position; specific funding details are not disclosed in the announcement.

Funding details

The position is a paid postdoctoral appointment at MIT, initially for one year starting September 2026, with the possibility of renewal for a second year. No specific stipend or salary amount is mentioned.

What's required

Applicants must have a PhD in Computer Science or a closely related field, with hands-on experience training or fine-tuning large language models. Strong background in human-AI interaction, reinforcement learning, or AI alignment is required. Ability to advance research with minimal supervision is expected. Candidates should be interested in interdisciplinary work spanning HCI, ML, anthropology, and sociology. No specific GPA or language test requirements are mentioned.

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Professors

Associate Professor

University Name
Country flag

United States

Research Interests

Computer Graphics

Digital Art

Visualization Techniques

Data Visualization

User Experience Design

Professor

University Name
Country flag

United States

Research Interests

Sociology

Anthropology

Information Technology

Hci

Large Language Models

Professor

University Name
Country flag

United States

Research Interests

Large Language Models

Anthropology

Sociology

Computer Science

Reinforcement Learning

Professor

University Name
Country flag

United States

Research Interests

Hci

Anthropology

Reinforcement Learning

Large Language Models

Information Technology

Professor

University Name
Country flag

United States

Research Interests

Anthropology

Sociology

Hci

Large Language Models

Information Technology