Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- Germany
- Sweden
- United Kingdom
- Portugal
- Singapore
- Norway
- Italy
- Spain
- Netherlands
- Belgium
- Denmark
- Poland
- United Arab Emirates
- Australia
- Luxembourg
- Romania
- Ireland
- Canada
- Hong Kong
- Austria
- China
- Czech
- Worldwide
- Cyprus
- Estonia
- Finland
- Japan
- Malta
- Switzerland
- Greece
- India
- Morocco
- Slovakia
- Andorra
- Bulgaria
- Saudi Arabia
- Armenia
- Brazil
- Europe
- Mexico
- New Zealand
- 33 more »
- « less
-
Program
-
Field
-
many-body quantum systems, with applications to condensed matter physics, materials science, chemistry and related fields. The development of the concepts, algorithms and code libraries needed to advance
-
routine background checks. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms
-
laboratory from Université Côte d’Azur (UCA). He leads the eBRAIN research group and develops an interdisciplinary research activity on embedded bio-inspired artificial intelligence and neuromorphic
-
Control for System Engineering department includes the development of methods and tools for optimizing and controlling the dynamic behavior of systems in a wide range of application domains, in
-
generation initiative. Our laboratory has expertise in deep learning, including deep reinforcement learning, large language models, and the theory of deep learning. The candidate will develop DRL algorithms
-
-guided) Evolutionary trajectory analysis and fitness landscape modeling Integration of predictive algorithms with experimental iteration cycles High-throughput screening and selection platform development
-
of the algorithm for real-time planning in the event of unforeseen hazards or new demands. -Calibration and validation of the developed optimization-simulation coupling model with a fleet of robots ***FINANCIAL
-
of the observation receiver used to measure the transmitter output and extract distortion information. This position is part of the ERC Synergy DISRUPT project, which aims to develop new architectures for observing
-
machine. We develop quasi-Newton coupling algorithms for partitioned simulation of FSI, and we solve challenging FSI problems in the energy transition and in industry. This research is often in
-
Transfer Partnership (KTP) to develop advanced AI capabilities that will unlock the next level of market insights in the Kids, Parents and Family sector. Employed and supported by an academic team from