Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
staff members (one of whom could be the supervisor of your thesis/final project) who we may contact for references For more information regarding the topic of position, you are welcome to contact prof. dr
-
Requirements: Applicants should hold an MSc or Diploma in Engineering, Computer Science or a related discipline. Background in Machine Learning and Artificial Intelligence. Strong programming skills (Python
-
Society. The Department of Machine Learning and Systems Biology led by Prof. Dr. Karsten Borgwardt is looking to recruit a highly-motivated PhD student (m/f/d) for the project Building Clinical Foundation
-
this goal, it is paramount to characterize the added value of using machine learning in estimating and decoding quantum errors occurring in coded quantum systems. Research program: The PhD student will first
-
develop models that can read, extract and acquire knowledge from legacy data, coming both in the form of text and in the form of structured data (e.g. physical measurements) to predict characteristics
-
PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
-
Metal additive manufacturing process monitoring and control – Researcher, PhD position (ERC project)
of process condition variations. The important parts of the control system to be developed within this project are i) coaxial measuring of meltpool depth variations, and ii) machine learning-based models
-
will include boosted final states. The analysis strategy is strongly focused on advanced machine learning techniques, developing attention-based transformer models that will directly classify events from
-
, undergraduate and postgraduate education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en
-
renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks