Postdoc in Statistics in University of Connecticut – USA

Summary

The University of Connecticut (UConn) invites applications for a full-time Postdoctoral Research Associate in Statistics. The successful candidate will conduct innovative research in statistical methodology, machine learning, and learning techniques applied to complex biomedical and health-related challenges, with a focus on psychology, psychiatry, mental health, and aging. The position is under the mentorship of Dr. Ofer Harel and involves potential collaboration with medical and dental schools. The role is a 12-month, full-time contract, renewable annually for an anticipated 2-3 years, subject to performance and funding availability. Applicants must hold a PhD in Statistics, Biostatistics, Computer Science, Data Science, Information Science, or a closely related field by the start date. Strong analytical, computational, and communication skills are required. Applications close on October 23, 2026, with review beginning on the same date and continuing until the position is filled.

Key Facts

Department	Department of Statistics, College of Liberal Arts and Sciences
Position Type	Postdoctoral Research Associate
Discipline	Statistics
Research Area	Statistical methodology, machine learning, biomedical health, psychology, psychiatry, mental health, aging, medical imaging, electronic health records, knowledge graphs, graph machine learning, link prediction, representation learning, embeddings, probabilistic graphical models, causal relational inference, meta-research, scientometrics, scholarly communication, citation-based analysis, claim evidence modeling, evaluation research impact, novelty, large-scale scholarly datasets, infrastructure, corpus construction, entity resolution, graph databases, text-mining, NLP pipelines, research software, AI-assisted research workflows, LLM-supported literature synthesis, structured extraction, claims evidence, reproducible AI-in-the-loop pipelines, evaluation verification, model-generated outputs
Degree Required	PhD in Statistics, Biostatistics, Computer Science, Data Science, Information Science, or a closely related field
Experience	Demonstrated research experience in statistical and mathematical foundations relevant to modern data science; programming skills in Python and/or R; experience producing well-structured, user-friendly, reproducible research code; written and oral communication skills; ability to work effectively in an interdisciplinary team. Preferred qualifications include experience with knowledge graphs, graph machine learning, meta-research, scientometrics, large-scale scholarly datasets, research software development, and AI-assisted research workflows.
Funding	2-3 years funding, renewable annually based on performance and availability of funds
Contract Duration	Full-time, 12-month position, renewable annually for an anticipated 2-3 years
Language	English
Deadline	2026-10-23
Required Documents	Resume, Cover letter, Contact information of three professional references
Employer Address	UConn Storrs, Northeastern Connecticut, USA
Employer Contact	Mackenzie Murphy, [email protected]

About the Project

The research project focuses on developing and applying statistical methodology, machine learning, and learning techniques to address complex biomedical and health-related challenges. Specific areas of application include psychology, psychiatry, mental health, and aging. The project may also involve work with medical imaging and electronic health records. Preferred research interests include knowledge graphs, graph machine learning, link prediction, representation learning, embeddings, probabilistic graphical models, causal relational inference, meta-research, scientometrics, scholarly communication, and the development of research software and AI-assisted workflows for large-scale scholarly datasets.

Key Responsibilities

• Engage in innovative research addressing statistical methodology, machine learning, and/or learning techniques for complex biomedical and health-related challenges
• Work under the mentorship of Dr. Ofer Harel
• Potentially collaborate with Dr. Harel's collaborators across university medical and dental schools

Required Skills

• PhD in Statistics, Biostatistics, Computer Science, Data Science, Information Science, or closely related field (completed by start date)
• Demonstrated research experience in statistical and mathematical foundations relevant to modern data science (e.g., Bayesian/frequentist inference, information theory, uncertainty quantification, high-dimensional methods)
• Programming skills in Python and/or R
• Evidence of producing well-structured, user-friendly, reproducible research code (e.g., packages, documented pipelines, open-source contributions)
• Written and oral communication skills
• Ability to work effectively in an interdisciplinary team
• Experience with knowledge graphs, graph machine learning, link prediction, representation learning, embeddings, probabilistic graphical models, causal relational inference (preferred)
• Background/strong interest in meta-research, scientometrics, scholarly communication (including citation-based analysis, claim evidence modeling, evaluation research impact, novelty) (preferred)
• Experience working with large-scale scholarly datasets infrastructure (e.g., corpus construction, entity resolution, graph databases, text-mining, NLP pipelines) (preferred)
• Experience developing research software that supports end users (including web-based tools, platform features, APIs, dashboards, deployable prototypes) (preferred)
• Experience designing and using AI-assisted research workflows (e.g., LLM-supported literature synthesis, structured extraction of claims/evidence, reproducible AI-in-the-loop pipelines, evaluation/verification of model-generated outputs) (preferred)
• Evidence of strong collaborative instincts and experience engaging diverse faculty, students, and research stakeholders (preferred)

Who Should Apply

This position is suitable for individuals holding a PhD in Statistics, Biostatistics, Computer Science, Data Science, Information Science, or a closely related field, who have demonstrated research experience in statistical and mathematical foundations of modern data science. Candidates should possess strong programming skills in Python and/or R, excellent communication abilities, and a capacity for interdisciplinary teamwork. Those with a background or interest in knowledge graphs, graph machine learning, meta-research, scientometrics, large-scale scholarly datasets, research software development, or AI-assisted research workflows are particularly encouraged to apply.

About the Employer

The University of Connecticut (UConn) is ranked first among public universities in New England and among the top 20 nationwide. It is located in northeastern Connecticut, offering easy access to Boston and New York City. The Department of Statistics within the College of Liberal Arts and Sciences provides a vibrant and collaborative environment with exposure to a vast array of research areas.

Frequently Asked Questions

What is the duration of the postdoctoral position?

The position is full-time, 12-month, and renewable annually for an anticipated 2-3 years, subject to performance and availability of funds.

What is the latest possible start date for this position?

The latest possible start date for this position is Fall 2026.

What are the minimum qualifications required for this position?

Applicants must have a PhD in Statistics, Biostatistics, Computer Science, Data Science, Information Science, or a closely related field completed by the start date, along with demonstrated research experience in statistical/mathematical foundations and programming skills in Python and/or R.

Who will mentor the Postdoctoral Research Associate?

The Postdoctoral Research Associate will work under the mentorship of Dr. Ofer Harel.

What documents are required for the application?

Applicants need to upload a resume, cover letter, and contact information for three professional references.

When will the review of applications begin?

The review of applications will begin on October 23, 2026, and will continue until the position is filled.