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accurate, well-characterized methods that serve as traceable standards for biomarker quantification, enabling reliable and reproducible measurements across different assays. In this PhD project, you will
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. Your work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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temporal patterns across different neurons in the neocortical circuit and use them for closed-loop brain stimulation. By examining how these spatiotemporal dynamics relate to behaviour, you will develop new
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an innovative academic education to more than 20,000 students; conduct pioneering scientific research and play an important service-providing role in society. With more than 6000 employees from 100 different
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from the TexNet earth observation program or assets that provide quality data. Compare different methods and tools for deformation modelling. Engage in outside funding activities and promote programs
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Job Description If you are curious and proactive scientist with expertise and interest in computational biology and data science, and you are looking to make a difference working on projects
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spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication
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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon
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vessels and ship systems. Knowledge Graphs based on engine propeller combinator diagrams of the same vessels. Machine learning algorithms for data clustering and regressions of ship performance and
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of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e.g. random forest (RF