Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
-
are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
-
platform. Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research
-
implementing signal processing algorithms specifically tailored to analyze signals that contain interfering impulsive content, often encountered in data coming from main and pitch bearings. Machine learning
-
Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
-
of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
-
offer A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT researchers, giving you
-
the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
-
-driven approaches to health, society, and policy. BISI combines expertise in epidemiology, biostatistics, health economics, and machine learning to tackle complex societal challenges. BISI is actively
-
onboarding period that includes specialized courses and hands-on training in AI and machine learning. You'll also have the chance to explore different labs and core facilities, meet fellow researchers, and