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Z. Jason Ren

Top university

5 months ago

Environmental/Civil Engineering, Computer Science/Engineering, Data Science Princeton University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Expected salary range: Postdoctoral Research Associate $65,000–$71,000; more senior researcher $67,000–$86,000. Comprehensive benefits program available.

Deadline

Sep 7, 2026

Country flag

Country

United States

University

Princeton University

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Keywords

Computer Science
Data Science
Microbiology
Environmental Science
Carbon Capture And Storage
Artificial Intelligence
Civil Engineering
Energy Engineering
Python Programming
High Performance Computing
Carbon Accounting
Optimisation
Climate Resilience
Oil Recovery
Large Language Models
Machine learning

About this position


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Posted: Unknown

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Summary:

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Details

Posted: 07-Sep-25

Location: Princeton, New Jersey

Type: Full-time

Categories:


Other Staff/Administrative

Internal Number: 277839346


Position: Postdoctoral Research Associate
Description:

The Princeton University WET LAB (https://ren.princeton.edu/ ) is seeking a postdoctoral research associate(s) or more senior researcher(s) with expertise and interest in Large Language Models (LLM) for Energy Environmental Research and Applications. The researcher(s) will work with the principal investigator and team to develop, fine tune, and deploy LLM based tools for environmental engineering research, education, and industry use, particularly in energy saving, emission accounting, and resource recovery. We are seeking a highly motivated and organized researcher with the following qualifications:Responsibilities*Explore, collect, and preprocess various sources to develop domain LLM training and test datasets*Design and implement fine tuning and RAG workflows for LLMs on a variety of datasets*Maintain codebases and data pipelines; ensure reproducibility and version control*Work with team members to integrate LLM modules into user friendly decision support platforms*Facilitate user testing and gather feedback from research groups and industry partners*Draft and submit manuscripts, technical reports, and open source documentation for peer reviewed publications Qualifications*Ph.D. in Environmental/Civil Engineering, Computer Science/Engineering, Data Science, or a closely related field*Proficiency in Python or other tools and ML frameworks*Track record of open source contributions or tool development in AI/ML*Prefer to have hands on experience fine tuning LLMs and building RAG systems*Background with environmental engineering domains (energy auditing, GHG accounting, resource recovery)*Strong publication record and excellent written/verbal communication skills*Experience in coding for high performance computing (e.g., university cluster or similar systems) is desiredThe term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. The work location for this position is in-person on campus at Princeton University. This position is subject to the University's background check policy.To ApplyApplicants must apply online at https://www.princeton.edu/acad-positions/position/39382 and submit a CV, a one-page statement of research interests, and contact information for three references.


Expected Salary Range: PDRA: $65k - $71k :: ARS: $67k - $86k


The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.


The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.


Requisition No: D-26-ENE-00001


PI277839346


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About Princeton University
Princeton University is a vibrant community of scholarship and learning that stands in the nation's service and in the service of all nations. Chartered in 1746, Princeton is the fourth-oldest college in the United States. Princeton is an independent, coeducational, nondenominational institution that provides undergraduate and graduate instruction in the humanities, social sciences, natural sciences and engineering.As a world-renowned research university, Princeton seeks to achieve the highest levels of distinction in the discovery and transmission of knowledge and understanding. At the same time, Princeton is distinctive among research universities in its commitment to undergraduate teaching.Today, more than 1,100 faculty members instruct approximately 5,200 undergraduate students and 2,600 graduate students. The University's generous financial aid program ensures that talented students from all economic backgrounds can afford a Princeton education.
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Funding details

Expected salary range: Postdoctoral Research Associate $65,000–$71,000; more senior researcher $67,000–$86,000. Comprehensive benefits program available.

What's required

Applicants must hold a Ph.D. in Environmental or Civil Engineering, Computer Science/Engineering, Data Science, or a closely related field. Proficiency in Python or other programming tools and machine learning frameworks is required. Candidates should have a track record of open source contributions or tool development in AI/ML, preferably with hands-on experience fine tuning LLMs and building RAG systems. Background in environmental engineering domains such as energy auditing, greenhouse gas accounting, or resource recovery is preferred. A strong publication record and excellent written and verbal communication skills are expected. Experience in coding for high performance computing systems is desired.

How to apply

Apply online at https://www.princeton.edu/acad-positions/position/39382. Submit a CV, a one-page statement of research interests, and contact information for three references. Only complete applications will be considered. For more information, email [email protected].

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