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expertise in fire behaviour and climate modelling, remote sensing, and machine learning to a multidisciplinary research program that spans prescribed fire operations, fire behaviour modelling, IoT sensor
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. The successful applicant must also teach, supervise, prepare and participate in examinations, and fulfill other tasks requested by the Department. Assessment of applicants for the associate professorship will
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of the on-boarding programme, raising the awareness of newly hired lecturers, teachers and PhD students regarding approaches to learning, teaching and mentoring, and providing structured support to their integration
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Posting Close Date Qualifications Minimum Education and Experience ● PhD in Computer Science or related discipline. ● Has a proven track record of excellence in artificial intelligence/machine learning and
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of the multidisciplinary TrAI-SOC project, coordinated in collaboration with UGA's CERAG laboratory. SocSIM-K: https://lig-socsim-k.imag.fr/ LIG: https://www.liglab.fr/en Activities Design the game and define all of its
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will contribute to the design, development and delivery of Accounting modules and programmes, together with the development of teaching and learning strategies relevant to Accounting and its related
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(payable 14 times per year) Responsibilities The applicant is expected to establish an own research group with focus on advanced machine learning and deep learning techniques for remote sensing applications
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applications in any era or area of specialization. The successful candidate must have a record of excellence in research and scholarship; be prepared to teach undergraduate and graduate courses in U.S. Women’s
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studies have demonstrated the limitations of current ground- and satellite-based observational networks. The PhD project aims for a new method to derive ground-level concentrations from satellite-based
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. The Department of Internal Medicine has 211 faculty who are actively involved in research activities and supervise biomedical learners, including PhD and master’s students, to gain in-depth experience in high