Sort by
Refine Your Search
-
Listed
-
Employer
- ICN2
- Institut de Físiques d'Altes Energies (IFAE)
- Fundació Hospital Universitari Vall d'Hebron- Institut de recerca
- Centre for Genomic Regulation
- Institut Català de Nanociència i Nanotecnologia
- Universitat de Barcelona
- ASOCIACIÓN INSTITUTO DE INVESTIGACIÓN SANITARIA BIOGIPUZKOA
- Agencia Estatal Consejo Superior de Investigaciones Científicas (CSIC)
- Aridditive
- Autonomous University of Madrid (Universidad Autónoma de Madrid)
- BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
- Barcelona School of Economics
- Computer Vision Center
- Consejo Superior de Investigaciones Científicas
- Fundació Privada Institut d'Investigació Oncològica de Vall d'Hebron (VHIO)
- IMEDEA-CSIC-UIB
- Institut d'Investigacio Biomedica de Bellvitge (IDIBELL)
- Institut de Robòtica e Informàtica Industrial CSIC-UPC
- Nature Careers
- Universidad Politecnica de Cartagena
- Universidad Pontificia Comillas
- Universitat Autònoma de Barcelona
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- Universitat Pompeu Fabra
- Universitat de Girona
- University Miguel Hernandez
- universitat de barcelona
- 17 more »
- « less
-
Field
-
-position-deep-sea-ecological-modelling Work Location(s) Number of offers available1Company/InstituteInstitut de Ciències del Mar (ICM), CSIC, BarcelonaCountrySpainCityBarcelonaGeofield Contact State/Province
-
the Computer Vision Center at the Universitat Autònoma de Barcelona; the CVC is a center with over 150 persons working machine learning and computer vision research. The position is for 3 to 3.5 years, starting
-
Relativity, and cosmological measurements using GWs such as Hubble constant and probes of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep
-
assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
-
assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
-
Relativity, and cosmological measurements using GWs such as Hubble constant and probes of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep
-
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
-
to develop and implement machine learning/deep learning tools for personalized medicine in cancer by exploiting electronic medical records and medical images in relation to cancer diagnosis and the
-
characterization techniques. · Knowledge: Deep expertise in electron microscopy, particularly STEM and FIB methods. Proven experience in designing and conducting in-situ TEM experiments. Familiarity with energy
-
. Familiarity with statistical modelling, machine learning and deep-learning Additional information: We offer: 🌐The opportunity to work with our state-of-the-art HPC infrastructure and to join a vibrant network