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. The research area will focus on “Precision Nutrition in Obesity, Diabetes and Food Insecurity for Health Equity” using large datasets from various sources including the collection from original research work. The postdoctoral fellow will also be engaged in laboratory 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 as needed. The AIPrN program also provides professional development and career pathways to independent research opportunities.

This position is appointed for a minimum of two years but no more than three years, with renewal after the first 12 months based on performance; further extension of the appointment is possible, 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 research background in conducting human subjects research in obesity, diabetes, food insecurity, and/or precision nutrition.
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.

 Preferred Qualifications:

1. Experience developing interventions and related research studies in nutrition health disparities or health equity, precision nutrition science, dietary intake assessment, microbiome-host-disease relationships, biomarkers, underserved populations, minority, rural and urban health, community-engaged health behavior interventions and/or mHealth technologies.
2. Experience with data analysis or statistics (quantitative and/or qualitative), including knowledge and skills in statistical tools, and software.

Completion of an RD-MS or equivalent dietitian program is desirable.

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

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

Apply clicking on this link: https://pvamu.co1.qualtrics.com/jfe/form/SV_8GoYwDDmx5CBp8W

Program background

The Increasing and Diversifying Future AI-Precision Nutrition Research Workforce to Promote Nutrition Health Equity among Underserved Populations 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 disparities, and food insecurity/hunger. The purpose of this research training is to support the development of a diverse 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.

Background Check Requirements:

All positions are security sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s veri?cation of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check.

Equal Opportunity/Af?rmative Action/Veterans/Disability Employer committed to diversity.