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are looking for an ambitious candidate with a strong background in mathematical and statistical methods for both physics-based modelling and machine learning, and their application to engineering problems in
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for candidates to have the following skills and experience: Essential criteria PhD at or near completion in at least one of the following subjects: Computer Science, Machine Learning, Biomedical Engineering
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energy systems; wireless and photonics systems, semiconductors, RF, and devices; AI and machine learning; advanced computing, cyber-physical systems and bioengineering. The department is housed within
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lectures on the following modules: Analog Signals and Systems (45AH) Digital Signals & Systems (45AH) Machine Learning (45AH) Operating Systems/Computer Architecture (45AH) Computer Vision/Image Processing
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network models on computing clusters Knowledge, Skills and Abilities: Demonstrated fluency in Python, and willingness to keep up with new machine learning libraries (pytorch, lightning, …) Knowledge
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of Computer Systems. A successful candidate will be expected to lead a research team of graduate students as well as teach at the undergraduate and graduate levels. The position is open to individuals with a
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individuals with a PhD degree from a recognized university and with substantial expertise in Machine Learning. Qualified candidates will be recruited according to their academic accomplishments
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behavioural, physiological, and environmental acoustic variables. This post would suit someone with a PhD in biomedical engineering, data science, machine learning, experimental psychology, audiology, cognitive
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employing standard and advanced statistical methods, including machine learning algorithms. The incumbent will also pursue independent research interests, secure extramural funding, and contribute to academic
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assessments (EMA), and passively monitored behavioural, physiological, and environmental acoustic variables. This post would suit someone with a PhD in biomedical engineering, data science, machine learning