Sort by
Refine Your Search
-
and capability gaps. Learning Objectives: Through this opportunity, you will gain knowledge and practical experience in biosurveillance, emerging biological threats, public health preparedness, program
-
managing diabetes using computer simulation models. Learning Objectives: You will learn: How to synthesize and translate empirical evidence on cost-effectiveness of interventions for the prevention and
-
machine learning methods, including cluster analysis and predictive modeling, to identify distinct phenotypes of diabetes and characterize factors associated with disease onset, progression, complications
-
to multidisciplinary research aimed at advancing military medicine. What will I be doing? This opportunity offers a hands-on learning experience within a collaborative research environment focused on combat casualty
-
technology or Artificial Intelligence (AI) tools to solve business or administrative problems, demonstrated knowledge with Machine Learning (ML) and AI tools. Strong integration experience in enterprise
-
the shallow subsurface (<10 meters depth). Experience with soil moisture/salinity and sapflow sensors. Experience using neural networks and machine learning tools. Stipend $70,000.00 – $80,000.00 Yearly Point
-
nucleic acid extractions, amplicon sequencing, data management and analysis. You will learn how to identify risks and improvement opportunities, ensure compliance with established policies and agency
-
the guidance of your mentor, you will study Fusarium Head Blight (FHB), one of the most significant diseases affecting wheat production, grain quality, and food safety worldwide. You will learn how
-
are highly desirable. Familiarity with data science and machine learning applications for analytical chemistry, industrial/agricultural facilities, and techno-economic or life-cycle analysis is considered a
-
chronic conditions and illnesses. This research aligns with CVDB's public health mission to strengthen evidence supporting improved recognition and characterization of ME/CFS. Learning Objectives: You will