Sort by
Refine Your Search
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- Utrecht University
- Eindhoven University of Technology (TU/e)
- Leiden University
- University of Amsterdam (UvA)
- University of Twente (UT)
- European Space Agency
- Maastricht University (UM)
- University of Groningen
- University of Twente
- Wageningen University & Research
- Computer Vision Center
- Radboud University
- Radboud University Medical Center (Radboudumc)
- SRON
- Universiteit Leiden
- 6 more »
- « less
-
Field
-
initiatives, and establish standards to advance machine learning ( OpenML.org ) OpenML is a popular open science platform for sharing interconnected AI artifacts (e.g., datasets, models, and benchmarks) using
-
inference), and automated machine learning. holding (or close to acquiring) a PhD degree in Computer Science, Artificial Intelligence or a closely related field; strong research vision and an academic mindset
-
. What you bring We are looking for candidates with: A PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or a closely related field; A strong publication record in
-
interested in mentoring and supporting MSc and PhD students. You are a machine learning enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present
-
; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
-
scholars, communication scholars, digital humanities and computer scientists. Experience with organising workshops, lecture series, and similar events. A PhD degree in Law, Political science, Information
-
energised — not deterred — by problems that sit between physics, learning and the messy real world. Your experience and profile: a PhD (completed or near completion) in Machine Learning, Computer Vision
-
, with a particular focus on the iron and steel sector. By using TROPOMI observations with advanced machine learning techniques, the project will provide independent information on emission patterns and
-
partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across the two teams. The position offers a strong publication trajectory at leading HCI venues
-
theoretical challenges motivated by astrodynamics, optimisation, control, scientific machine learning, mission design and autonomous systems, translating these into new research directions in deep learning