Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Universidade de Vigo
- University of A Coruña
- UNIVERSIDAD POLITECNICA DE MADRID
- Universidad de Alicante
- IRTA
- Institute for bioengineering of Catalonia, IBEC
- Universitat Autonoma de Barcelona
- Universitat Politècnica de València
- Agency for Management of University and Research Grants (AGAUR)
- CIC nanoGUNE
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- Centre for Genomic Regulation
- IMDEA Networks Institute
- ISGLOBAL
- Instituto de cerámica y vidrio
- Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM) - Universidad Politécnica de Madrid (UPM)
- Universitat Autònoma de Barcelona
- University of Deusto
- 8 more »
- « less
-
Field
-
, integrated circuit designers, and quantum algorithm developers Analyze and interpret experimental data, contributing to scientific publications, patents, and presentations. Engage with the wider international
-
simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
-
generate, transmit, and detect OAM-entangled photons under realistic atmospheric turbulence. Deep learning algorithms will be employed to pre-compensate distortions in real time, maximizing state fidelity
-
batteries, along with advanced sensor systems. A key focus is micro integrating energy sources and sensors into autonomous, self-powered platforms by leveraging standard silicon technologies, rapid
-
-sensitivity cortisol sensor for biomedical applications and emotional monitoring Where to apply E-mail doctorats.industrials.recerca@gencat.cat Requirements Research FieldEngineeringEducation LevelMaster Degree
-
for precision livestock farming within the Horizon Europe Re-Livestock project. The candidate will design and analyse mathematical algorithms to monitor and improve animal performance, welfare and environmental
-
STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 119977 Development of mathematical and machine-learning algorithms to support an intelligent, integrated system for biosafety
-
genetics Programs This research develops early warning systems and resilience indicators in swine using high-frequency sensor data from commercial farms. Integrating environmental, behavioural, feeding, and
-
techniques and neural network techniques to adjust high-resolution X-ray spectra and infer physical properties of the emitting plasma. · Developing algorithms that optimise the adjustment of high-resolution X
-
/Qualifications Experience in: - Development of artificial intelligent algorithms. - Explanaible artificial intelligence - LLM experience - Virtual intelligence entities using reinforced learning