"Postdoctoral Position in Artificial Intelligence and Precision Nutrition"

Postdoctoral Position in Artificial Intelligence and Precision Nutrition

Company: Prairie View A&M University

Job Location:

Category: Nutrition and Dietetics

Type: Full-Time

College of Agriculture, Food and Natural Resources & College of Engineering at Prairie View A&M University

USDA-ARS Children’s Nutrition Research Center at Baylor College of Medicine

Position location: College of Agriculture, Food and Natural Resources at Prairie View A&M University

Position type: 12-month stipend consist with NIH and Prairie View A&M University guidelines

Stipend amount: Commensurate with experience (childcare and insurance are additional benefits)

Application deadline: Open until filled

The selected postdoctoral research fellow for this Artificial Intelligence in Precision Nutrition (AIPrN) position will be stationed at the College of Agriculture, Food and Natural Resources at Prairie View A&M University to work under the direction and primary mentorship of Dr. Janet Antwi with additional advising from a second primary mentor in AI including machine learning (ML), computational or data science analytic approaches. Depending on the focus of the precision nutrition project, the postdoctoral fellow when necessary, will engage in rotations with a multi-disciplinary team at Prairie View A&M University and at our partnering institution, the USDA-ARS Children’s Nutrition Research Center at Baylor College of Medicine for additional trainee’s research experience in the research area. Projects will use large datasets from various sources including the collection from original research work. The AIPrN program also provides professional development and career pathways to independent research opportunities.

This position is appointed for two years, and may be extended to a third year but no more than three years, with renewal after the first 12 months based on performance; further extension of the appointment is contingent on funding availability from individual fellowships (F32 NRSA) and/ or other research grants.

Required Qualifications and Duties:

1. Must be a citizen or a noncitizen national of the United States or have been lawfully admitted for permanent residence at the time of appointment.
2. PhD in a relevant discipline (e.g., nutrition, dietetics, public health, health psychology, or a related discipline) or MD at the time of appointment.
3. Appropriate background in conducting human subjects research.
4. Experience in grant writing, manuscript publications, project management, and mentoring of students.
5. Excellent written and oral communications skills.
6. Perform other related duties and participate in special projects as assigned.

Please direct your questions to Dr. Janet Antwi at jaantwi@pvamu.edu

Apply through the application link below, and submit your CV, and personal statement describing previous achievements, research interests, career goals, and why you are suitable for this position.

Apply by copy pasting this link: https://pvamu.co1.qualtrics.com/jfe/form/SV_8GoYwDDmx5CBp8W

Program background

The Increasing Future AI-Precision Nutrition Research Workforce to Promote Nutrition and Health program is an NIH T32 Advanced Training in Artificial Intelligence for Precision Nutrition Science (AIPrN) Research Training Program to address diet-related chronic diseases, nutrition health outcomes, and food insecurity/hunger. The purpose of this research training is to support the development of research workforce of predoctoral students and postdoctoral fellows who will possess advanced competencies in AI/ ML to apply innovative transdisciplinary approaches to an increasingly complex landscape of Big Data on nutrition and diet-related chronic diseases. Precision nutrition is a comprehensive and dynamic scientific approach to tailoring nutritional recommendations to an individual’s circumstances and biological characteristics. Precision nutrition integrates big datasets of genetics, gut microbiome, metabolism, dietary patterns, physical activity, physiology and metabolic patterns, underlying health status, behaviors, socioeconomic and psychosocial influences, and environmental exposures to promote, maintain health and prevent chronic diseases. Thus, precision nutrition is an advancement on traditional dietary advice. Recent rapid advances in use of Artificial Intelligence (AI), Machine Learning (ML), Systems Biology, Systems Science, Big Data, and computational analytics for integration and analyses of complex high-dimensional big datasets offers unparalleled opportunities to assess these numerous individual characteristics in precision nutrition interventions.

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