Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- NTNU - Norwegian University of Science and Technology
- Radboud University
- Wageningen University & Research
- University of Amsterdam (UvA)
- Utrecht University
- Aalborg University
- CNRS
- Delft University of Technology (TU Delft)
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- Grenoble INP - Institute of Engineering
- Instituto de Sistemas e Robótica (ISR)
- Monash University
- NTNU Norwegian University of Science and Technology
- The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences
- Trinity College Dublin
- UNIVERSITAT POMPEU FABRA
- University of Bergen
- University of Potsdam •
- University of South-Eastern Norway
- jobs.ac.uk
- 11 more »
- « less
-
Field
-
planning and decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch
-
; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting pathogen invasion success and plant
-
decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
-
, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
-
decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
-
of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research, responsible
-
experts on dynamical systems and ergodic theory, postdoctoral researchers Josias Reppekus and Misha Hlushchanka, both active in different areas of complex dynamical systems. PhD students and postdoctoral
-
, physiology and disease development; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting
-
or environmental engineering, Mathematics (Operations research) or Computer Science or Machine Learning). Documented knowledge of relevant methodologies, both quantitative and/or qualitative, at master’s level
-
Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in