Sort by
Refine Your Search
-
Listed
-
Country
- United States
- United Kingdom
- France
- Germany
- Sweden
- China
- Canada
- Italy
- Spain
- Denmark
- Belgium
- Poland
- Singapore
- Australia
- Finland
- Austria
- Portugal
- Macau
- Netherlands
- Lithuania
- Morocco
- Japan
- Mexico
- Ireland
- South Africa
- United Arab Emirates
- Worldwide
- Hong Kong
- India
- Taiwan
- Switzerland
- Czech
- Greece
- Latvia
- Luxembourg
- Norway
- Andorra
- Armenia
- Barbados
- Bulgaria
- Estonia
- Europe
- Israel
- New Zealand
- Romania
- 35 more »
- « less
-
Field
- Medical Sciences
- Economics
- Computer Science
- Engineering
- Business
- Biology
- Science
- Education
- Materials Science
- Psychology
- Mathematics
- Arts and Literature
- Social Sciences
- Chemistry
- Law
- Humanities
- Linguistics
- Sports and Recreation
- Environment
- Philosophy
- Design
- Earth Sciences
- Electrical Engineering
- Physics
- Statistics
- 15 more »
- « less
-
modeling framework, which we use to assess the industry transition of the three basic materials: steel, cement, and plastics. It consists of the dynamic material flow analysis model REMIND-MFA, tracking
-
: 87647BR Supervises staff involved in providing clinical patient care. Assists in ensuring the quality of patient care delivery in a specific patient care area and serves as a role model for professional
-
”) on the development of material flow analysis (MFA) methods and digital methods for spatial analysis. Specific tasks comprise: Design and apply digital models for analyzing and simulating circular futures
-
at the surface of various materials. Key Responsibilities: Perform quantum mechanical calculations (DFT) for establishing reaction mechanisms and kinetics Develop and apply advanced computational models to predict
-
and Failure of the Surface-Stress "Core-Shell" Model in Brookite Titania Nanorods. Chemistry of Materials, 2020. 32(1): p. 286-298. Ab initio theoretical modeling; Active nanodevices; Atomic scale
-
Scientist Position #: 00845968 – Requisition #:39260 Job Summary: Our laboratory develops translational models of transplantation and regeneration to study immune responses, neuronal connectivity, and tissue
-
interaction with materials, as well as surface reaction kinetics based on kMC-type descriptions. The main activities include: (1) the development of efficient surrogate models of kMC-based surface kinetics
-
NIST only participates in the February and August reviews. The fire modeling community is actively working to develop the tools needed to quantitatively predict material and product flammability
-
, and Azure—and designs future-state structures that support data products, analytics, automation, and AI/ML enablement. Establishes enterprise data standards, models, governance structures, and
-
thermodynamic descriptions to model diffusion processes in a variety of disordered and ordered metallic systems. The next challenge is to model the diffusion mobilities in complex materials where a Calphad-type