45 computer-science "The Forest Science and Technology Centre of Catalonia (CTFC)" research jobs at University of New South Wales
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Apply now Job no:524007 Work type:full time Location:Sydney, NSW Categories:Post Doctoral Research Associate Post-Doctoral Fellow (Implementation Science) Employment Type: Full - time (35 hours a
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Apply now Job no:523384 Work type:full time Location:Sydney, NSW Categories:Research Administration support Research Assistant (School of Biomedical Sciences) Employment Type: Full - time (35 hours
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skills to contribute effectively to the research efforts of CHeBA and UNSW. Skills Required: A PhD in Neuroimaging, Data science, Engineering, or a related field or a recently submitted PhD thesis with
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, Biomathematics, Biostatistics and Ecology, Combinatorics, Computational Mathematics, Data Science, Dynamical Systems and Integrability, Finance and Risk Analysis, Fractional Calculus, Functional and Harmonic
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. A person engaged is generally expected to have the following skills and experience: Experience working with a range of computer systems. Candidates with experience relevant to international students
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collaborative research with a focus to enhance the quality of research outcomes in Genomics & Computational Biology. Conduct research (as per the norms of the discipline) and/or enable research teams to create
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) in biostatistics, epidemiology, public health, computer science, psychology or a related discipline, and/or relevant work experience. Demonstrated track record of research in a health-related area
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: www.imos.org.au), responsible for the ongoing operation of the ocean-observing programme along south-eastern Australia. The position will primarily provide numerical modelling and software engineering support for
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techniques, including differential equations, computational methods, stochastic processes, and optimisation theory. We are currently working on a program of research focussing on transmission models
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/photovoltaic-and-renewable-energy-engineering/our-research/research-activities/characterisation-defects-machine-learning Skills & Experience: A PhD in Computer Science or a related field. Thorough theoretical