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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
Machine Learning (DM3L) Doctoral Candidate in computer vision and machine learning for developing novel deep learning methods for satellite-based tracking of global CO2 and NOX emissions of point sources 80
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transfer, developing and employing laboratory experiments, computer simulations, and field analyses. Our aim is to gain fundamental insights and to develop sustainable technologies that address societal
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assistant professorship or a tenured associate professorship in Structural Biology, Biophysics or Biological Imaging. We encourage applications from candidates who explore fundamental questions in biology
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-ray diffraction and even more specifically to XRD-PDF (pair distribution function). The project is linked to crystalline and amorphous alloys, and in an industrial context to process design by
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core part of your project will be interpreting the data and developing scientific hypotheses about the atmospheric processes that control the cycling of selenium and other trace elements. You will work
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limited to: • Analog and mixed-signal circuit design, including radio-frequency (RF) and millimeter-wave circuits, for communication, sensing, imaging, and signal processing; • Low-power
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100%, Basel, fixed-term The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational
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property analysis, sorting, and grading. Contribute to the TIMBERHAUS project by applying advanced image processing and AI methods for timber quality assessment. Integrate experimental data with
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application process, please contact the Office of the Dean (dekanat-philnat@unibas.ch ). The deadline for receipt of applications is November 3, 2025. The University of Basel is an equal opportunity and family
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candidates to apply for a post-doctoral position in Biomedical Research investigating allergic, immunologic and metabolic processes. The candidate will join a multi-disciplinary team focusing