Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Portugal
- Netherlands
- France
- Germany
- Sweden
- Spain
- Belgium
- Norway
- Denmark
- Italy
- Singapore
- Morocco
- Australia
- Finland
- Switzerland
- Czech
- United Arab Emirates
- Poland
- China
- Ireland
- Canada
- Austria
- Romania
- Luxembourg
- Japan
- Brazil
- Estonia
- Hong Kong
- Andorra
- Bulgaria
- Croatia
- Greece
- Lithuania
- Malta
- Saudi Arabia
- Slovenia
- 28 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Environment
- Chemistry
- Business
- Psychology
- Humanities
- Linguistics
- Education
- Electrical Engineering
- Law
- Physics
- Arts and Literature
- Social Sciences
- Philosophy
- Sports and Recreation
- Statistics
- 14 more »
- « less
-
the collection of empirical data through field trials and the development of prediction models based on these data. The candidate is to perform a variety of functions related to research. The candidate is expected
-
the collection of empirical data through field trials and the development of prediction models based on these data. The candidate is to perform a variety of functions related to research. The candidate is expected
-
- research experience in the evaluation of global wave reanalysis and integration of topographic and bathymetric datasets, as well as experience in the implementation of XBeach and SWaN models. Preferential
-
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in the prediction and modelling of extreme flood events? Do you want to understand how
-
natural and human disturbances through climate-smart forestry startegies, based on observations and predictive models. Where to apply Website https://unimol.concorsismart.it/ Requirements Additional
-
: Kinetic stability data collection for predictive bioprocess modelling of CYP enzymes PhD enrolment: Technical University of Denmark DC4: ML-guided evolution of peroxygenases for selective C-H
-
complex, high dimensional and high-volume datasets. Uses data preparation, modeling and predictive modeling, analysis, processing, algorithms, and systems. Applies knowledge of statistics, machine learning
-
of the SU(N) Fermi-Hubbard model and its low-temperature phases at the microscopic level. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=1003
-
Sharing – Building a federated data space to enable responsible data integration and cross-project learning. AI & Modelling – Using shared data to power advanced models that help describe and predict
-
, and c) predicting new phenomena and discovering improved materials for applications. My efforts in this area use a variety of modeling approaches to answer questions on materials systems of interest