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(working as part of a team), and attention to detail. Experience in programming multiple languages (Python, MATLAB, Simulink, C++, VBA, etc) Some experience in developing machine learning models Demonstrated
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Application Deadline 24 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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, their spouse, and children at the end of their contract. School tuition fees for children to attend the K-12 program in Vietnam, up to $20,000 per child or $40,000 for two children per year. Premium private
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using Large Language Models (LLM) to query and reason geospatial data. The project aims to develop a pilot decision support systems in collaboration with industry partners. The Postdoctoral Research
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teaching for both undergraduate and postgraduate students. The program courseware is accredited by the Global Accreditation Centre of the Project Management Institute. It builds the capacity of graduates
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networks. The candidate needs to have a strong background in ML programming, particularly large-scale models, and working with LLM. Familiarity with system security and anomaly detection is desirable. To be
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. The ideal candidate will also be expected to have quantifiable experience with: A variety of different neuroimaging methodologies. Using multiple programming languages, including R, Python, MATLAB and
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at seminars and/or scientific meetings Strong written and oral communication skills Advanced computing skills including in programming in R You will bring your strong research expertise to a multi-disciplinary
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, QAQC procedures and data analysis experience with ‘R’ programming language excellent fish identification skills fish dissection experience, including otolith analysis analysis of video data from marine
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for independent work as well as team focused demonstrated ability of interpersonal, written, and oral communication skills demonstrated ability to prioritise and manage multiple tasks in a busy environment. Pre