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learning control. The overall goal of this PhD project is: To develop and integrate adaptive spiking circuits based on organic neuromorphic and biohybrid devices. Embedding The PhD student will be directly
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with hardware architecture, FPGA, and system-level simulation is desirable. A good theoretical understanding of statistics and machine learning theory. Strong analytical skills and proficiency in
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-making processes. Moreover, recent developments in the field of machine learning have established a strong connection between these structures and neural networks, which we seek to fortify by developing
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of the coupling using a data-driven approach. The deviation between healthy and pathological pregnancies will be detected through machine learning tools. These tools will be integrated into a clinical decision
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Irène Curie Fellowship No Department(s) Mechanical Engineering Reference number V35.7384 Job description ASML Photolithography machines play a central role in the production of ever smaller and
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Irène Curie Fellowship No Department(s) Mechanical Engineering Reference number V35.7383 Job description ASML Photolithography machines play a central role in the production of ever smaller and
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presented thus far. Many solutions involve machine learning to learn the environment. However, by looking deeper into known properties of radio propagation in multipath environments, our first insights
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Irène Curie Fellowship No Department(s) Electrical Engineering Reference number V36.7298 Job description PhD project description Novel and innovative technologies like automated and autonomous
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and behavioural theory of travel choice demand. Discrete choice modelling, integrated modelling, and machine learning methods for travel behavior analysis. Agent based simulation. If you're passionate
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stochastic flow networks? Are you excited about an opportunity to teach and supervise students in the area of Applied Probability and Stochastic Operations Research? We offer a PhD-TA position (75% research