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of older persons. The candidate will also contribute to teaching activities related to machine learning or other areas depending on the candidate’s profile. Moreover, the candidate is a team player that
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RNA-Seq, ChIP/DAP-Seq protein-DNA interaction data, bulk, and single-cell ATAC-Seq) and the application of diverse supervised machine learning approaches (e.g., feature-based, deep learning, and
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within the IN-DEEP project you will be at the forefront of developingnew hybrid machine learning (ML) accelerated solvers. A fast-expandingarea of research is the application of ML techniques to predict
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fundamental knowledge of, this domain. Be sure to mention in your motivation letter any knowledge of (or previous experience with) the machine learning research topics of the PhD project as detailed in
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. NERF is a joint research initiative by imec, VIB and KU Leuven. The project We are looking for a PhD candidate interested in developing machine learning methods and applying them to neuroscience problems
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of debiased machine learning methods. This PhD project will primarily focus on the foundations of an assumption-lean modeling paradigm, with a strong focus on the analysis of repeated measures outcomes, in
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. ESAT of KU Leuven (Belgium). The goal of this research is to develop new machine learning methods for the quality assessment and enhancement of signals and annotations in time series data, with
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have taken specialized courses in some of the following disciplines: digital signal processing, audio signal processing, machine learning, and/or machine listening. Research experience (e.g. through
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You have a master's degree in Computer Science, Artificial Intelligence or similar. You are interested in Logic, Machine Learning, Knowledge Graphs, Stream Processing, the Internet of Things, Edge
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, these methods are more and more combined with machine learning techniques. BIONAMIX is a team embedded in the department of data analysis and mathematical modelling in the Faculty of Bioscience engineering. We