Sort by
Refine Your Search
-
Listed
-
Employer
- Virginia Tech
- Cornell University
- Argonne
- Northeastern University
- Oak Ridge National Laboratory
- Texas A&M University
- The Ohio State University
- Baylor College of Medicine
- Brookhaven National Laboratory
- Duke University
- Lawrence Berkeley National Laboratory
- Massachusetts Institute of Technology
- Massachusetts Institute of Technology (MIT)
- National Aeronautics and Space Administration (NASA)
- North Carolina A&T State University
- Pennsylvania State University
- SUNY University at Buffalo
- South Dakota Mines
- University of California, Merced
- University of Central Florida
- University of Miami
- Zintellect
- 12 more »
- « less
-
Field
-
design theory that facilitates multi-objective, multi-disciplinary optimization of data center design considering location, building operations, materials, energy use, water use, cooling system design, and
-
initiatives include developing advanced aqueous emulsion and suspension systems for spray coating, predictive modeling of packaging performance, and optimizing packaging designs for high-value product
-
, cold chain logistics, and sustainable packaging systems, addressing critical challenges in product protection, supply chain optimization, and distribution system efficiency. We seek a highly motivated
-
. The researcher will also design data-driven numerical approaches to address a variety of real-life optimization models including disaster and emergency logistics, supply chain and transportation. Specific
-
-of-the-art experimental techniques, innovative methodologies, and/or numerical models to make fundamental advances to existing literature. Duties will include but are not limited to: Helping develop novel
-
numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually. Required Qualifications • PhD in agricultural and
-
machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
-
breeding is the introgression of numerous identified disease resistance genes into single lines useful for further breeding and improvement through the development and use of rapid-cycling grape germplasm
-
to have a Ph.D. in Applied Mathematics, Mathematics, Control, Operations Research, Statistics, or a related field. Experience in numerical analysis, scientific computing, and either optimization or machine
-
systems. The individual will be responsible for: • Develop and implement models for the structural and mechanical performance and optimization of mass timber systems, using data-driven approaches