18 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" scholarships at University of Twente (UT)
Sort by
Refine Your Search
-
on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
-
and international partners. Where to apply Website https://www.academictransfer.com/en/jobs/358420/phd-position-in-micro-robotics/… Requirements Specific Requirements You hold a Master’s degree in
-
, electrical engineering or simila,r with an affection for machine learning; You are an independent and original thinker with a creative mindset; You are a fast thinker with excellent analytical and
-
doing their final assignment on sub-projects pertaining to the current research project. The PhD research will be performed in the Production Technology group. Where to apply Website https
-
emerging field with your insights. You will learn how to design chemical reaction networks at material interfaces and become a forerunner in chemically-programmable coatings. Briefly, the core objective of
-
universities and companies, within the National Growth Fund program Circular Batteries. Where to apply Website https://www.academictransfer.com/en/jobs/357796/phd-position-within-the-project… Requirements
-
Website https://www.academictransfer.com/en/jobs/357989/add-ream-3-phd-positions/apply/ Requirements Specific Requirements A Master’s degree in Mechanical Engineering, Materials Science, Industrial
-
companies in living labs, contribute to workshops and consortium meetings, and help ensure that your results are usable in practice (not only published). Where to apply Website https
-
matters of scientific urgency. Where to apply Website https://www.academictransfer.com/en/jobs/357678/phd-position-in-project-mechani… Requirements Specific Requirements We look for an enthusiastic
-
these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based