Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- Autonomous University of Madrid (Universidad Autónoma de Madrid)
- Barcelona Beta Brain Research Center
- Basque Center for Macromolecular Design and Engineering POLYMAT Fundazioa
- 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 SANITARIA PERE VIRGILI
- Institut Català de Nanociència i Nanotecnologia
- Institut d'Investigacio Biomedica de Bellvitge (IDIBELL)
- Institut de Robòtica e Informàtica Industrial CSIC-UPC
- Universidad Politecnica de Cartagena
- Universidad Pontificia Comillas
- University Miguel Hernandez
- University of A Coruña
- universitat de barcelona
- 6 more »
- « less
-
Field
-
to the topic, including food safety, microbiology, computational biology, machine learning, artificial intelligence, data science, or other related scientific fields. Familiarity with data-driven
-
=50415 Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Advanced skills in Machine Learning and Artificial Intelligence Proficiency in spoken and written English
-
expertise in machine learning or computational modelling who are eager to advance conceptual innovation toward practical industrial deployment. Qualifications PhD in Computer Science, Machine Learning
-
of Spanish (not required but valued for teaching and policy dissemination in Spain). Experience with AI-based research workflows, machine learning techniques applied to financial data, or modern
-
-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona. The QML-CVC team (https://qml.cvc.uab.es /) is part of
-
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
-
development of analytical solutions, data analysis and machine learning. Candidates should have a demonstrated record of scientific publications in international journals and participation in conferences
-
biological environments - Experience using machine‑learning algorithms for luminescence signal analysis and sensing applications - Experience writing scientific articles and presenting results at conferences
-
, including Machine Learning Interatomic Potentials. • Other research experience will be considered. Personal Competences: • Strong commitment • Attention to detail • Demonstrated ability to work with deadlines
-
clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep