Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nanyang Technological University
- University of Oslo
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Harvard University
- Indiana University
- University of British Columbia
- University of South-Eastern Norway
- City of Hope
- Humboldt-Universität zu Berlin
- Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S)
- Northeastern University
- Politécnico de Leiria
- TAIPEI MEDICAL UNIVERSITY (TMU)
- THE UNIVERSITY OF HONG KONG
- Universidade do Minho
- University of Algarve
- Yale University
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- Carnegie Mellon University
- Centro de Engenharia Biológica da Universidade do Minho
- Cornell University
- Cranfield University
- Dana-Farber Cancer Institute
- FEUP
- Faculdade de Ciências da Universidade de Lisboa
- Institute for Basic Science
- Instituto Nacional de Investigação Agrária e Veterinária, I.P.
- Johns Hopkins University
- LINGNAN UNIVERSITY
- Lawrence Berkeley National Laboratory
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Max-Planck-Institut für Bildungsforschung
- National University of Singapore
- Paul Scherrer Institut Villigen
- Queen's University Belfast
- SUNY University at Buffalo
- Tampere University
- UiT The Arctic University of Norway
- University of Aveiro
- University of Basel
- University of Bergen
- University of Colorado
- University of Idaho
- University of Inland Norway
- University of Leeds
- University of North Carolina at Chapel Hill
- University of Notre Dame
- University of Waterloo
- Vanderbilt University
- Virginia Tech
- Zintellect
- 41 more »
- « less
-
Field
-
help industrial firms use operational data in new ways, for example to improve fuel efficiency, support predictive maintenance, enhance safety, reduce emissions and optimize the use of resources. In
-
: Define the critical engineering requirements (optical pulse duration, terahertz crystal materials in cryogenetic environments, signal-to-noise ratio optimization, entanglement witnesses and verification
-
will have a practical understanding of the other function’s responsibilities to enable them to be an optimal collaborator and colleague. During the fellowship, the fellow will work within Regulatory
-
solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Independently
-
well as strategies for improving performance by optimization of composition, microstructure, and the interface to the proton-conducting electrolyte. The content of the PhD Research Fellowship can be tailored according
-
physical latency limits and human perceptual tolerances. The work will comprise designing networking and computing architectures that integrate prediction and control algorithms, optimizing data
-
range of methodological approaches is relevant for the theme, including qualitative case studies, optimization models, system dynamics modelling, and agent-based modelling. Please note that the project
-
and targeted, computationally expensive, model simulations. This experimental design process is envisioned to update iteratively as new data become available to optimally infer surface fluxes across
-
in chemistry and biology, approaches for extracting relevant information from foundation models, and/or methods for adaptive experimental design such as active learning or Bayesian optimization
-
reporting procedures for any incident or event that did affect or potentially could affect the project goals and workflow. Optimize protocols and improve methods currently employed. Coordinates work