Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- UNIVERSIDAD POLITECNICA DE MADRID
- Fundació per a la Universitat Oberta de Catalunya
- Autonomous University of Madrid (Universidad Autónoma de Madrid)
- CIC energiGUNE
- INSTITUTO DE ASTROFISICA DE CANARIAS (IAC) RESEARCH DIVISION
- Barcelona Supercomputing Center (BSC)
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- Computer Vision Center
- FUNDACIO INSTITU DE RECERCA EN ENERGIA DE CATALUNYA
- FUNDACIÓN CANARIA PARQUE CIENTÍFICO TECNOLÓGICO
- Fundació Hospital Universitari Vall d'Hebron- Institut de recerca
- ICN2
- IRTA
- Institute for bioengineering of Catalonia, IBEC
- Institute of Photonic Sciences
- Instituto de Neurociencias de Alicante, CSIC-UMH
- Universidad de Alicante
- Universidad de León
- Universitat Pompeu Fabra
- Universitat Pompeu Fabra - Department / School of Engineering
- University of A Coruña
- 11 more »
- « less
-
Field
-
. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group: Atomistic & Molecular Modelling for Catalysis Group Requirements Specific Requirements PhD in Chemistry
-
, computer science, bioengineering, data science, or a closely related discipline. • Demonstrate advanced proficiency in artificial intelligence and machine learning, particularly in applications involving
-
transcriptomics data analysis. Experience in quantitative image analysis, computer vision, or digital pathology. A strong background in cancer biology or immunology. Experience with machine learning, deep learning
-
Leonardo. The successful candidate will play a crucial role in developing and optimizing machine learning workflows for large-scale environmental data analysis, contributing to the creation of robust and
-
. We will analyse systems based on deep reinforcement learning and transfer learning, as well as distributed architectures that use federated learning. This work package outlines the tasks required
-
machine learning model for domain adaptation in brain image analysis and reconstruction. Development of a platform for the collection, harmonization, and processing of hospital data. Definition
-
Requirements Experience in the development of software solutions that allow the anonymization or pseudonymization of named entities and sensitive data. Machine learning/deep learning training. Good level of
-
general ability and affinity to using computer tools and programs. We employ tools and create methods, so abilities to handle tools and willingness to learn more are needed. LanguagesENGLISHLevelExcellent
-
Computer engineering, Data Science, Mathematics or equivalent, with focus on energy modelling and electricity markets. Proven experience (>2 years) in energy systems modelling, machine learning or artificial
-
sequences, networks, trajectories, images, etc. - Design, programming, optimization, and parallelization of machine learning algorithms. - Search in repositories and bioinformatics of DNA sequences