339 machine-learning-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" positions in Netherlands
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- DIFFER; Published yesterday
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); Published 21 Nov ’25
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- Tilburg University; 16 Oct ’25 published
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- University of Amsterdam (UvA); Published 14 Nov ’25
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approaches. What we ask of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow
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of data scientists, data engineers, software developers and many more, that are focused on bringing data, machine learning and statistical modeling into the products that we build for our clients
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needed. You have experience in advanced bioinformatic analyses of omics datasets, preferably single cell and/or long read RNAseq data. Demonstrable experience in advanced machine learning and/or high
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. Through our bachelor’s and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging Technologies & Societal Transformations, Resilience
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on bringing data, machine learning and statistical modeling into the products that we build for our clients or internal users. The data scientists in INGA furthermore have a strong desire to keep up with and be
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, and prototyping. Lead education with workshop tools and machines. Lead the academic aspects of operation and management of the engineering technical learning spaces in collaboration with the laboratory
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become better versions of themselves. At BMS we do this through academic education, fundamental science and societal problem-solving. From Bachelor’s or Master’s degrees and Professional Learning
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& Educational Affairs ensure that Vrije Universiteit Amsterdam works like a well-oiled machine. We assist in logistics and help with realising educational programmes; we also aim to create a worry-free and
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willingness to learn Dutch. We prefer that you are proficient in scientific computing (Python, Matlab, R, and UNIX), have strong data processing and collection, and are familiar with the basics of machine
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develop models that can read, extract and acquire knowledge from legacy data, coming both in the form of text and in the form of structured data (e.g. physical measurements) to predict characteristics