Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- University of A Coruña
- CNRS
- Institute for bioengineering of Catalonia, IBEC
- Nature Careers
- Universidad de Alicante
- University of Innsbruck, Institute of Computer Science
- University of Luxembourg
- University of Texas at Austin
- Brookhaven National Laboratory
- CIC nanoGUNE
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- Charles University, Faculty of Mathematics and Physics
- Columbia University
- Edmund Mach Foundation
- FCiências.ID
- Heidelberg University
- Institute for Basic Science
- Institute of Nuclear Physics Polish Academy of Sciences
- Leibniz
- NTNU Norwegian University of Science and Technology
- Newcastle University;
- RAEGE-Az
- Susquehanna International Group
- The University of Iowa
- UNIVERSIDAD POLITECNICA DE MADRID
- UNIVERSITY OF HELSINKI
- Universidade de Coimbra
- University of Groningen
- University of Jyväskylä
- University of New Hampshire
- University of Newcastle
- University of Texas at El Paso
- University of Tübingen
- Universität Siegen
- 24 more »
- « less
-
Field
-
title: UDC-Inditex Chair of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient Grant/funding period: START: 01
-
26 Nov 2025 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique de Toulouse Research Field Computer science Mathematics » Algorithms Researcher Profile First
-
anticipated include imaging phantom-based evaluation of quantitative SPECT/CT; reconstruction algorithm development; establishing a secondary standards laboratory for unsealed source metrology through gamma
-
(ECLECTX team). This person occupying this position is planned to work on modeling computing elements, established and emerging, at different levels of abstraction, design and development simulation tools
-
involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build more trustworthy and robust AI models that can
-
goals include optimising convective heat transfer using wall oscillations, relating small-scale turbulence to heat transport, modelling large-scale outer flow effects, and developing low-order heat
-
research focused on biomedical image computing. Our work involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim
-
of these activities is for the scholarship holder to develop new knowledge and skills in Artificial Intelligence, with an emphasis on the development of methodologies and techniques in Evolutionary Computation and
-
Computer Science• Distributed systems (Cloud, Edge)• Scheduling and optimization algorithms• Data streams, data management and data pipelines• software engineeringExpert programmer• Java• at least one other
-
), physics-informed generative modeling and representation learning, domain adaptation, ML-assisted lattice field theory, and quantum algorithms and Hamiltonian simulation for high-energy physics, etc