Sort by
Refine Your Search
-
Employer
- Fundació Hospital Universitari Vall d'Hebron- Institut de recerca
- Institut de Físiques d'Altes Energies (IFAE)
- Institut Català de Nanociència i Nanotecnologia
- Universitat de Barcelona
- BARCELONA SUPERCOMPUTING CENTER
- BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
- Biobizkaia Health Research Institute
- Consejo Superior de Investigaciones Científicas
- FUNDACIO INSTITU DE RECERCA EN ENERGIA DE CATALUNYA
- IMEDEA-CSIC-UIB
- Institut de Robòtica e Informàtica Industrial CSIC-UPC
- UNIVERSIDAD POLITECNICA DE MADRID
- Universidad Nebrija
- Universidad Politecnica de Cartagena
- Universidad Pontificia Comillas
- Universitat Autònoma de Barcelona
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- Universitat Pompeu Fabra
- Universitat de Girona
- universitat de barcelona
- 10 more »
- « less
-
Field
-
Nanotools is a research group based at Vall d’Hebron Hospital (Barcelona, Spain). Our aim is to develop and validate novel detection strategies with diagnostic purposes https://vhir.vallhebron.com/es
-
. Recognised Researcher position has been opened. The ideal candidate holds a master's-level background in robotics, AI or related fields, with strong Python/C++ skills and experience in machine learning
-
of Robotics and Industrial Informatics (CSIC-UPC) offer a position to work on World Models for Human Behaviour Anticipation https://ramonllull-aira.eu/archivos/theme_field/world-models-for-human-behaviour
-
the interplay between mutations, energetics, and evolutionary constraints, including epistatic effects. · Developing or applying machine learning approaches to predict or redesign frustration patterns in proteins
-
based on neutral atom platforms, exploring both theoretical and experimental domains. Research will span quantum control, quantum-enhanced machine learning, and hybrid quantum-classical computation
-
) participate in the monitoring at sea to acquire video and picture of the transplanted sites, (2) quantitatively analyse video to define species and functional diversity, species abundances and population size
-
to the topic, including food safety, microbiology, computational biology, machine learning, artificial intelligence, data science, or other related scientific fields. Familiarity with data-driven
-
to the publication of the call for applications: https://seu.ub.edu/ofertaPublicaCategoriaPublic/listPublicacionsAmbCategoria?categoria.id=855899 Where to apply Website http://www.ub.edu/caiac/solBeca?idConvocatoria
-
and paleosols 3) train and test deep learning algorithms. You will be required to take responsibility for all the steps involved in the “Phytolith analysis” work package of DEMODRIVERS. This will
-
platforms. Experience in development of digital twins or physics-informed machine learning models. Experience in programming (e.g., Python or equivalent) and development of control or data acquisition