Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Nature Careers
- UNIVERSIDAD POLITECNICA DE MADRID
- ICN2
- Universidad de Alicante
- Barcelona Supercomputing Center (BSC)
- Fundació per a la Universitat Oberta de Catalunya
- Universidade de Vigo
- Autonomous University of Madrid (Universidad Autónoma de Madrid)
- FUNDACIO INSTITU DE RECERCA EN ENERGIA DE CATALUNYA
- Fundació Hospital Universitari Vall d'Hebron- Institut de recerca
- Fundación IMDEA Software
- IDIVAL
- ISGLOBAL
- Institut d'Investgació i Innovació Parc Taulí (I3PT)
- Institute for bioengineering of Catalonia, IBEC
- UNIOVI
- UNIVERSIDAD PUBLICA DE NAVARRA
- Universidad Carlos III de Madrid
- Universidad de León
- University of Lleida
- 10 more »
- « less
-
Field
-
dedicated to discovering and refining the core mechanisms that will enable machines to learn continuously, make robust decisions in complex environments, and evolve autonomously. Key research directions
-
and preparing the devices for the next group. SPECIFIC DUTIES Programming the sensors at the beginning of day. Distributing sensors to participants and ensuring they are used properly. Collecting
-
nature of the tasks involved. About the UOC A leader in e-learning, our pioneering university is a digital native with global reach and a mandate for public service. We've been providing accredited, high
-
Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and
-
characterization, and integration of machine learning to correlate synthesis conditions with functional performance. The goal is to establish predictive synthesis strategies for oxygen vacancy control, with
-
Machine-learned force field Metamaterials (nanophotonics, metamaterials/metasurfaces, and metamaterial-enabled optical computing) If you are a passionate and innovative scientist or researcher eager to make
-
are not limited to: Machine Intelligence, AI for Science, Scientific Computing, Robotics, Complex Systems Modeling, Control, and Decision Making, Autonomous Agent and Multi-Agent Learning, Computational
-
of artificial intelligence (AI) and biomedical engineering. Research directions include deep learning, natural language processing, brain–computer interfaces, and their applications in disease prediction, drug
-
-based learning, synthesis testing, and user testing. Actively promoting the integration of technology and industry, the Laboratory has taken the lead to establish a National Bio-manufacturing Innovation
-
Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
Personal Competences: Demonstrated competitive ability in using DFT simulations, and machine learning techniques and DFT. Demonstrated strong coding skills and a passion for UX/UI design. Summary