45 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Delft University of Technology (TU Delft) in Netherlands
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27 Feb 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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10 Apr 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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of the following subjects: scalable data management, systems for machine learning, distributed and parallel systems, or cloud-based systems. We are especially interested in researchers who build working systems and
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track record in one or more of the following fields: (1) human-computer interaction, collaborative AI, (2) Generative AI/machine learning, (3) interaction design, experimental design, or evaluation
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industry. You will teach and supervise Bachelor, Master, and PhD students in Computer Science programs. In addition, you will play an active role in the cybersecurity scientific community by publishing
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Computational Design and Fabrication for Human Computer Interaction (HCI
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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to learn more about the project, and perhaps our group? Feel free to browse our webpages: About our department: QCE department . About our group: Computer Engineering Lab . Job requirements For this position
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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). Experience applying statistics and Machine/Deep Learning to real-world data. Experience working with manufacturing process data, robotics systems and/or metrology data (sensor data, quality data, measurement