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Field
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consider novel design principles combining approaches in biosensors, communication systems, and machine learning. Are you motivated to take a step towards a doctorate and open up exciting career
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with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs, recovery of dual-comb measurement signals and
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engineering, data science, or related fields Strong programming skills (especially in Python), and experience with simulation, modelling, data analysis, machine learning, and hardware control Solid
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biology, or analytical workflows. Interest in single-cell analysis, cancer biology, and translational research. Basic level expertise in computational biology (e.g., bioinformatics, machine learning), with
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; - Background in Electrical Engineering / Computer Engineering / Mathematics and expertise in Artificial Intelligence and Machine Learning, Electronic Design Automation or Analog and Radio Frequency IC Design are
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these sounds fascinating, then this PhD position is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning
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quantitative modeling; Strong expertise in programming, including proficiency in languages commonly used in data analysis and machine learning, such as Python; Excellent verbal and written communication skills
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human perception and cognition. Experience in: experimental methods, computer rendering or VR/XR, programming. Affinity with multidisciplinary work, combining science, art, and technology. Enthusiasm
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photonics or electrical engineering or applied physics or similar. Experience with machine learning, digital signal processing and experimental work is a plus. Further obligations: The doctoral candidate (DC
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) and satellite platforms, and surface energy balance models will be used to obtain evapotranspiration (ET); computer vision and machine learning techniques will also be used to identify and count fruits