Aaaipress
Overview
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.
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 desired
Appointment Details The 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.
How to Apply Applicants 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.
Salary and Benefits Expected Salary Range: PDRA: $65k - $71k; ARS: $67k - $86k
The University considers factors such as 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.
#J-18808-Ljbffr
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 desired
Appointment Details The 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.
How to Apply Applicants 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.
Salary and Benefits Expected Salary Range: PDRA: $65k - $71k; ARS: $67k - $86k
The University considers factors such as 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.
#J-18808-Ljbffr