355 web-developer "https:" "https:" "https:" "Fraunhofer Gesellschaft" positions at NIST
Sort by
Refine Your Search
-
We develop and utilize state-of-the-art experimental and computational techniques to acquire, evaluate, and correlate thermodynamic data of standard reference quality with a particular emphasis on
-
, and light-matter interactions. This research opportunity is focused on developing compact, integrated cavity optomechanical devices that push the state of the art in terms of sensitivity and accuracy
-
Density Functional Theory (DFT)—frequently fail to balance the necessary accuracy with the required computational scale. Our group is developing a high-performance computational framework to bridge this gap
-
301.975.3507 Description Recent developments in Artificial Intelligence (AI) have allowed machine learning models to solve certain complex problems in natural language processing and other areas at large scales
-
to the sub-nanometer scale regime. Our goal is to leverage our access to state-of-art X-ray and neutron facilities to develop and apply operando measurement methods that can quantify full three-dimensional
-
to consider multidimensional landscapes. The goal of this research project is to develop models that can be used to evaluate the stability and predict transitions as cell populations progress from pluripotent
-
developing the measurement infrastructure to acquire fundamental property data related to the capture and release of difficult to detect drugs or drug metabolites. We will then design, develop, and
-
are particularly interested in developing and characterizing hybrid quantum systems (interfaces between dissimilar physical media), suitable for quantum information purposes, and exotic sources of faint light
-
identification of spectral features by computer vision and machine learning. Our computational methods development has three primary goals. The first goal is continued support of expert-driven biomolecular
-
properties. While our focus is on industrially important fluids, such as fuels and refrigerants, we also welcome proposals that would yield data primarily intended for model development, such as studies