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mathematical modelling, with a focus on real-world applications. This includes statistics, uncertainty quantification, data analysis, signal processing, (mathematical foundations of) machine learning, and
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processing, (mathematical foundations of) machine learning, and dynamical systems. Your job In this position, you will divide your time roughly equally between research and teaching (approximately 50% each
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-antibodies. You will focus on the identification of these antibodies by using mass spectrometry based de novo sequencing, machine learning and AI-tools to interpret the data. Your job The primary objective
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mass spectrometry based de novo sequencing, machine learning and AI-tools to interpret the data. Your job The primary objective of the project is to further develop mass spectrometry-based techniques
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unique opportunity to contribute to the technological foundations for tomorrow’s machine learning. Your job In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential
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-based knowledge with machine learning. You will work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop and implement surrogate and hybrid modelling
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: 12 September 2025 Apply now Are you a data scientist interested in designing and implementing process-informed machine learning and uncertainties quantification methods? Join us as a postdoc and work
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Specific Requirements We expect you to have A master’s degree (or equivalent) in urban planning/urbanism/architecture, computer science, human-computer interaction, or related field. Interest and experience
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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