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Postdoctoral Fellow in Artificial Intelligence and Precision Nutrition

Job Description

Position ID:Cornell -DNS -POSTDOCFEL [#25315, WDR-00038819]
Position Title: 
Position Type:Postdoctoral
Position Location:Ithaca, New York 14853, United States [map ]
Subject Areas: Bioinformatics / Computer Science
Data Science / Data Science and Information
Salary Range:$56,880 - $75,000
Appl Deadline: (posted 2023/08/14, updated 2023/08/11, listed until 2023/12/31)
Position Description:  Apply    

Postdoctoral Fellow in Artificial Intelligence and Precision Nutrition - Cornell University

The Cornell NIH T32 Training Pro gram in Artificial Intelligence and Precision Nutrition, AIPrN, is seeking applications for a Postdoctoral Fellow. The AIPrN training program represents the first institutional training grant focused on the intersection of Artificial Intelligence and nutrition and is supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health.

The training program is designed to train the next  generation of scientists and build a workforce equipped with expertise in Artificial Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in nutrition and health using high dimensional data. The program will bring together faculty from Cornell University’s Ithaca, Cornell Tech, and Weill Cornell Medicine campuses, West Point, and University of California San Diego from the fields of nutrition, medicine, health and biomedical sciences, computer and information sciences, data science, engineering, and bioinformatics with core competencies in computational methodology, data science, systems science, ML, AI, and data infrastructure.

To be eligible, trainees must:

1.  Be a U.S. citizen, non-citizen U.S. national, or those lawfully admitted for permanent residence.

2.  Have received a PhD in computer science, information science, bioinformatics, mathematics, or a related data science field. 

Candidates should demonstrate quantitative/qualitative research skills, excellent written and oral communication skills, and the ability to work independently and with collaborators. A track record of original first-author publications or conference proceedings from doctoral work is desirable. 

The T32 program requires dual mentorship - trainees will need to choose one mentor from the nutrition or related biomedical fields category and a second one from the computer and information science field listed on this page . Trainees will be expected to focus on questions related to AI and precision nutrition for their research and participate in a capstone course on this topic.

The selected candidate will be paid a 12-month stipend consistent with NIH and Cornell guidelines. Postdoctoral fellows also may apply for additional pilot funds from the Center for Precision Nutrition and Health to conduct research (up to $20,000) and/or present at professional conferences, as well as to support registration for online conferences.

Applicants must submit a NIH Biosketch or curriculum vitae through Academic Jobs Online https://academicjobsonline.org/ajo/jobs/25315 .

Applications will be reviewed on a rolling basis. Applicants who are moved beyond the first screening will be asked to submit additional information.

Please direct any questions to precision-nutr@cornell.edu .  

The Division of Nutritional Sciences, and the College of Human Ecology and the College of Agriculture and Life Sciences at Cornell embrace diversity and seek candidates who will create a climate that attracts faculty, staff and students of all races, nationalities, and genders. We strongly encourage members of underrepresented groups to apply. In addition, Cornell University seeks to meet the needs of dual‐career couples, has a dual‐career program, and is a member of the Upstate New York Higher Education Recruitment Consortium to assist with dual‐career searches. 

Familiarize yourself with Cornell’s COVID-19 workplace guidance as well as the university’s COVID-19 services and information .

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