Sort by
Refine Your Search
-
Listed
-
Employer
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- UNIVERSIDAD POLITECNICA DE MADRID
- University of A Coruña
- IE University
- Universitat de les Illes Balears
- ARQUIMEA RESEARCH CENTER
- BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
- Consejo Superior de Investigaciones Cientificas
- Institute for bioengineering of Catalonia, IBEC
- UNIVERSIDAD DE GRANADA
- Universidad de Alicante
- 1 more »
- « less
-
Field
-
Infrastructure? No Offer Description Mission: Participate in the development of high-performance Shallow Water models. Functions to be developed: To develop a tool for baroclinity simulation of the atmospheres
-
to researchers with a strong background in applied and computational mathematics who develop mathematical models and numerical methodologies for scientifically relevant problems. The successful candidate will
-
HRER2026/357-222 Perfil R1 para desarrollo de algoritmos de IA / R1 profile to develop AI algorithms
. // Software development for the European project SkincAIr. Desarrollo de algoritmos de IA para la detección de enfermedades tropicales desatendidas // Development of AI algorithms for the detection of Neglected
-
and simulation of physical, engineering, or complex systems. The position is particularly suited to researchers with a strong background in applied and computational mathematics who develop mathematical
-
multidisciplinary robotics, involving visible, infrared and event-based sensing technologies. The selected candidates will contribute to the design, development and validation of advanced computer vision algorithms
-
, DMC). Development and implementation of Quantum Monte Carlo algorithms. Numerical simulation of many-body quantum systems. High-performance computing (HPC) and Linux environments. Scientific programming
-
systems, autonomous vehicle control, robotics, numerical simulation and the ability to develop algorithms in research environments will be an advantage. - PROFESSIONAL EXPERIENCE. 50 % Prior experience
-
Mission: Support research to improve the management of renewable energies. Functions to be developed: Develop machine learning algorithms. Implement and validate computational models. Plan networks with
-
tradespace explorations for optimal constellation design. Software contribution: Develop and release open source modules for the Orekit library. Where to apply Website https://seuelectronica.upc.edu/en
-
learning y deep learning para el análisis de datos de observación de la Tierra. Application of machine learning and deep learning algorithms for Earth Observation data analysis. 5. Manejo de plataformas