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-type specific samples, state-of-the-art molecular biology techniques, multimodal data generation and integration, gene regulatory network reconstruction and wide range of machine learning approaches
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and Computer Engineering with specialization in Information Systems, which will allow a broad spectrum of interdisciplinary research. In particular, the successful candidate will be part of the E
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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
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modeling into modern causal inference by combining its strengths with innovations in debiased machine learning, as well as to improve both the statistical efficiency and robustness of debiased machine
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programming. You are highly motivated to conduct (applied) research at the intersection of (deep) machine learning and the health sciences. You have good programming skills in languages such as Pythorch, and
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are looking for a m/f/x Doctoral fellow YOUR JOB You conduct doctoral research in the area of Augmenting Learning Environments Using Generative AI and Neuroadaptive Systems, with the aim to obtain a PhD after
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relationships. You are motivated to acquire new skills and work in a multidisciplinary team. You have practical experience with experimental work and data analysis. You act with attention to quality, integrity
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are curiosity-driven especially interested in interdisciplinary research, eager to continuously learn with critical thinking and explore new ideas while collaborating with a team Language Skills: Fluent written
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collaborative project with other PhD students, postdocs and technical assistants. How to apply How to apply To apply, please send us the following documents, merged into a single PDF file: A one-page cover letter
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interdisciplinary research team, focusing on human-robot interaction, unconventional robotics, cognitive systems and machine learning. You will have access to the full facilities of IDLab, including high-performance