Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- Virginia Tech
- NEW YORK UNIVERSITY ABU DHABI
- Delft University of Technology (TU Delft)
- Stony Brook University
- Aarhus University
- Cornell University
- Purdue University
- Technical University of Denmark
- University of Nevada, Reno
- Villanova University
- Aalborg Universitet
- Aalborg University
- Delft University of Technology (TU Delft); Published yesterday
- Duke University
- Durham University
- ETH Zürich
- GFZ Helmholtz-Zentrum für Geoforschung
- Ghent University
- Institute of Theoretical Physics
- International Iberian Nanotechnology Laboratory (INL)
- Oak Ridge National Laboratory
- Stanford University
- Texas A&M AgriLife
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); Published today
- University of Maine
- University of North Carolina at Chapel Hill
- University of Southern California
- University of Southern California (USC)
- University of Washington
- 21 more »
- « less
-
Field
-
). This position focuses on the machine learning methodology of the project, aiming to: Develop probabilistic spatio-temporal models that integrate uncertainty from climate projections into land-use forecasts
-
well as international partners. Field experiments, digital technologies - including modelling and remote sensing, as well as interactions with stakeholders are key components of Land-CRAFT. You will be part of a research
-
Job Description We offer an opportunity for a motivated researcher to contribute to advancing our understanding of how Earth's upper atmosphere interacts with space. The successful candidate will
-
well as international partners. Field experiments, digital technologies - including modelling and remote sensing, as well as interactions with stakeholders are key components of Land-CRAFT. You will be part of a research
-
development of standard and deep sub-micron process nodes design flow and translate the key physical parameters from models to design kits to support full integration of such advanced devices in CMOS processes
-
system optimization for remote construction. This position will focus on advancing research in construction assembly science and technology, logistics optimization, and real-time communication frameworks
-
imaging cameras in advanced silicon technologies. Your work will push the boundaries of high-frequency sensing and integrated EM design. Job description In the Tera-Hertz Sensing (TS) Group at TU Delft, you
-
Join the Tera-Hertz Sensing Group to develop next-generation THz imaging cameras in advanced silicon technologies. Your work will push the boundaries of high-frequency sensing and integrated EM
-
vibratory extraction and jetting, supported by experiments at multiple scales and advanced numerical modelling. By studying ageing effects on extractability and predicting mechanical responses, the project
-
atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address fundamental scientific challenges, including global cloud