Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Netherlands
- France
- Germany
- Spain
- Australia
- Sweden
- Portugal
- Italy
- Singapore
- Norway
- Canada
- Belgium
- Poland
- Austria
- Denmark
- China
- Switzerland
- United Arab Emirates
- Japan
- Ireland
- Luxembourg
- Finland
- Hong Kong
- New Zealand
- Czech
- Romania
- India
- Brazil
- Morocco
- Macau
- Saudi Arabia
- Greece
- Mexico
- South Africa
- Croatia
- Estonia
- Bulgaria
- Cyprus
- Malaysia
- Slovenia
- Hungary
- Latvia
- Malta
- Taiwan
- Europe
- Iceland
- Israel
- Lithuania
- Qatar
- South Korea
- Vietnam
- 43 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Biology
- Engineering
- Business
- Science
- Mathematics
- Psychology
- Materials Science
- Education
- Chemistry
- Environment
- Arts and Literature
- Social Sciences
- Earth Sciences
- Humanities
- Electrical Engineering
- Law
- Linguistics
- Sports and Recreation
- Philosophy
- Physics
- Design
- Statistics
- 15 more »
- « less
-
. The research project focuses on the design, development and validation of Artificial Intelligence and Machine/Deep Learning models applied to healthcare, with particular reference to computer vision applied
-
; • mathematical modelling, development of FEM models (preferably using Ansys), and simulations, particularly in the areas of electromagnetics, power losses, etc.; evaluation, verification, and optimization
-
advanced statistical modelling, econometrics or machine learning with a particular focus on analysing large-scale behavioural data? Are you interested in developing new methodological approaches capable
-
- Experience in modelling aquatic systems - Fieldwork experience - Ability to interact with non-scientific stakeholders Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5175-AXEGAY
-
). The role combines quantitative epidemiology, mathematical modelling and field epidemiology. The post holder will undertake epidemiological and statistical analyses of field data, contribute
-
Connallon): Meta-analysis and modelling of why additive genetic variance for fitness is so high, and what it means for adaptation and population viability (no prior modelling experience needed). (Lab: https
-
CNRS. The supervisory environment will bring together expertise in the humanities and social sciences, anthropology, climate modelling and computer science, with Patricia Cadule, Philippe Hunel and
-
patient outcomes. More information about the lab can be found here: https://www.nathlab.org As a successful candidate, you will: Develop AI/ML models to predict patient outcomes, treatment response, disease
-
limited to, riverine, estuarine, and coastal systems; surface and subsurface hydrology; transport processes and sediment dynamics; coupled human-water systems; hydrologic prediction and modeling across
-
the interplay between quantum mechanics and gravity in the low-energy regime, with particular emphasis on theoretical and phenomenological models in which gravity is described as a quantum, semiclassical, or