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Field
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++ programme “Break-through technologies in flow and fluid composition measurement”. It involves close cooperation with flow sensor companies and the TU Delft, where a post-doc will focus on the electronic
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researchers in soft robotics, control theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be
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interest in neuro-behavioral sciences and a passion for behavioral signals. Demonstrable experience in advanced data analysis and data collection. Familiarity with machine learning and proficiency in Python
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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at the interface of microbial ecology and advanced analytical technology. In our laboratories we have state-of-the art 3D printers and CNC machines as well as NMR spectrometers. Key responsibilities: Design and
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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artificial intelligence, computational cognitive science, human-computer interaction, computer science, information systems, or another relevant field. - A keen interest in pursuing interdisciplinary research
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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predicting and improving adherence through Artificial Intelligence (AI) and machine learning (ML). Your colleagues: An interdisciplinary team of scientists working across Maastricht University and FH Joanneum
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hold an MSc degree in environmental science or ecology, with a proven expertise in data analysis, organizing and handling. Expertise in machine learning is a plus. A sound command of the English language