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machine learning, signal processing, epidemiology and causal inference, but all candidates with knowledge at the intersection of these three scientific disciplines are invited to apply. Candidates with
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with your chip(s) will be analyzed with machine-learning algorithms. You will collaborate with researchers and companies of various disciplines like chemistry, embedded systems, software, signal
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tool into clinical decision-making and pathways, explore alternative pathways, evaluate acceptance and expected usability of multiplex sensors and machine-learning-based decisions and explore alternative
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. The data acquired with your chip(s) will be analyzed with machine-learning algorithms. You will collaborate with researchers and companies of various disciplines like chemistry, embedded systems, software
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machine learning model, we foresee using novel approaches for data fusion, such as linking information to gaze location and extracting coordination patterns between different modalities. You will work
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presentations at conferences) Demonstrable proactive and flexible attitude Has experience with molecular data and applying landscape modelling frameworks (e.g. SDMs) Particular strengths with Machine Learning
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other incident conditions, i.e., mainly higher incidence energies, which requires the development and implementation of a new machine-learning model to represent the tensorial electronic friction
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measurements, analytical- and physically-based models, as well as physics-informed machine learning/deep learning. Furthermore, you are expected to work together with partners in the Dutch water sector and help
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implications of such systems? We are seeking a postdoc to join our team, someone who is keen to contribute to the development of trustworthy machine learning systems and to translating algorithmic advances and
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who is keen to contribute to the development of trustworthy machine learning systems and to translating algorithmic advances and challenges in machine learning for policy makers. What are you going