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Field
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collaborative labs develop and deploy the latest technology, including sensing, data analytics, modelling, simulation, artificial intelligence, and machine learning, and function as dynamic hubs where innovative
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novel materials, tools, or artistic creations, humans instinctively explore the unknown in order to acquire information about it, to make sense of it, to act on it, and to appreciate what is in front of
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, development of data (pre-)processing pipelines, and machine learning model training to identify relevant biological states of the liver (e.g., healthy, recovering, not healthy). The (soft) sensor development
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, electrical engineering, technical medicine, or a related field. You have a solid background in biomedical signal analysis, physiology dynamic system, and machine learning technologies, and preferably have
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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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. Familiarity with machine learning and proficiency in Python or MATLAB. Excellent communication skills; proficiency in Dutch is desirable but not required. The capacity to thrive in a complex and dynamic
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such as model-based optimal control and nonlinear reset control. The goal is to push beyond commercial standards, achieving unprecedented sensitivity by overcoming mechanical and interferometric noise
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networks, or network science, and relevant background knowledge n methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods. Examples