Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
We have openings for two Assistant Professors to strengthen our position in the following fields: Machine Learning / Pattern Recognition Machine Learning / Generative AI Machine Learning / Pattern
-
described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
-
to develop your professional experience and competencies, to learn from ESA experts and to contribute to ESA activities. Technical competencies Experience with artificial intelligence and machine learning
-
(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure
-
for systematic reviews, Mendeley for citation management and SPSS for data/statistical analysis/machine learning. Diversity, Equity and Inclusiveness ESA is an equal opportunity employer, committed to achieving
-
Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
-
and strong preference for also excellent Dutch language skills. You’re able to adapt and learn quickly, you like to turn your ideas into action and are able to work independently. Strong detail
-
business card) Discount on membership of Erasmus Sport. Access to online learning platform GoodHabitz and wellbeing platform OpenUp. Regular fun work events and drinks. Participation in our collective
-
records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
-
in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any