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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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appropriate, development of reproducible computational workflows for processing and analyzing large genomic and immunologic datasets, visualization and communication of complex results to both computational and
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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difficult to access on near-term quantum hardware. The difficulty is that the relevant Hilbert spaces grow rapidly, the dynamics are non-Gaussian and nonlinear, and the circuits must be mapped carefully
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to develop a personal research programme in observational or theoretical cosmology, with a particular emphasis on ultra-large-scale cosmology (including primordial non-Gaussianity and horizon-sized effects
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and Gaussian state formalism. Quantum information theory and entanglement theory. Theory of spin-mechanical systems. Open quantum systems, continuous quantum measurement and feedback, and stochastic
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worldwide. In your cover letter or during your interview process, we invite you to share how your professional experiences have prepared you to serve as a member of our team as we work to reduce the cancer
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candidate with a disability, we are committed to ensuring fair treatment throughout the recruitment process. We will make adjustments to support the interview process wherever it is reasonable to do so and
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, multivariable regression, and/or high-dimensional biomarker analysis. Excellent written and oral communication skills. Demonstrated ability to work independently and collaboratively in a multidisciplinary
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Magdeburg, Sachsen Anhalt | Germany | 10 days ago
harmonizing clinical, cognitive, imaging, blood-based biomarker, and smartphone-based datasets across cohorts Developing and applying regression and linear mixed-effects