Sort by
Refine Your Search
-
Listed
-
Employer
- ICN2
- Institut de Físiques d'Altes Energies (IFAE)
- Universidad Politecnica de Cartagena
- Universitat Pompeu Fabra - Department / School of Engineering
- Universitat de Girona
- BARCELONA SUPERCOMPUTING CENTER
- Biobizkaia Health Research Institute
- CRAG-Centre de Recerca Agrigenòmica
- Consejo Superior de Investigaciones Científicas
- EURECAT
- FUNDACIO INSTITU DE RECERCA EN ENERGIA DE CATALUNYA
- Fundació Hospital Universitari Vall d'Hebron- Institut de recerca
- Fundació Sant Joan de Déu
- IMEDEA-CSIC-UIB
- Institut Català de Nanociència i Nanotecnologia
- Institut de Robòtica e Informàtica Industrial CSIC-UPC
- Nature Careers
- Universidad Nebrija
- Universidad Pontificia Comillas
- Universitat de Barcelona
- universitat de barcelona
- 11 more »
- « less
-
Field
-
and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries. Look at the BSC experience: BSC-CNS
-
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
-
insurance, public transport, training and car leasing) Wellness platform Flexible schedule and summer intensive workday 27 days of annual vacation Remote work Training and development Website for additional
-
AI4Science project, specifically focusing on the intersection of advanced machine learning and sustainable catalysis discovery. The primary incentive of this Postdoctoral Fellowship is the chance to contribute
-
software. (0-35) Experience in the application of advanced machine learning techniques (e.g., graph neural networks, reinforcement learning, probabilistic models, or latent representations) to biomedical
-
the neurovascular space. Knowledge of neurovascular anatomy, acute stroke, endovascular treatments, neuroendovascular devices for the treatment of stroke. Ability to generate machine learning analysis of medical
-
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
-
the development and assessment of neurotechnology aimed for invasive brain-computer interfaces. In particular, the work will include in vitro assessment of the performance of electrophysiology neural
-
. - Strong competence of maneuvering in the Terminal and in a High Performance Computer is desireable. The candidate will need to create its own environments to install multiple programs and launch jobs
-
experience with DFT codes will be very highly valued. • Knowledge of chemical reactions and how to model them through computer simulations is highly valued. • Knowledge of classical molecular dynamics