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requires: A licensed physical therapist with eligibility for licensure by the Nevada State Board of Physical Therapy Examiners. An earned terminal degree (PhD, DSc, or EdD) from a regionally accredited
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of inverse photonic design, machine-learning (adjoint or topology optimization), or other advancing design methodologies. Ability to design and model active photonic devices (MEMS, electro-optic or thermo
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or participation in funded projects. Expertise in AI and/or machine learning applied to health data. Experience of curriculum development and delivering high-quality and innovative teaching and assessment in higher
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populations in the context of nanohertz gravitational-wave observations Applying probabilistic inference to gravitational waves, including through machine learning techniques Analyse and interpret research
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genetically diverse mice under a multitude of conditions, and (3) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing
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Apply now Job no:536923 Work type:Faculty - Pro Tempore Location:Eugene, OR Categories:Instruction, Computer and Information Science, Data Science Department: CAS Data Science Rank: Instructor
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Science, Mathematics, Physics, Bioinformatics, or a related quantitative field Strong background and expertise in data science, bioinformatics, network science, artificial intelligence, machine learning, deep learning
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closely related discipline). You have a strong interest in AI/machine learning, data mining, regression analysis, responsible AI, causal inference, and programming (R/Python, SQL). Moreover, you are driven
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, or hold an equivalent qualification that allows enrollment as a PhD student at the University of Vienna by that date. Because we design and build our research machines ourselves, you must have extended
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer