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, alignment, and characterisation of laser-based instrumentation. • Strong experience with computer programming, both for signal processing and experimental hardware control (e.g., C, C++, Python, MATLAB
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admission to the programme, the candidate must document sufficient potential for research. The applicant must have a grade point average of C (strong 3.0) or better for the master’s degree, which must contain
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indicate whether you are applying at Level A or B, depending on your experience and qualifications. Please note we will be reviewing applications as they are received. Diversity is one of our greatest
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communication skills Commitment to mentoring graduate and undergraduate students Desirable (but not required): Experience with time-series QA datasets (e.g., Time-MQA, TSQA, MTBench) Background in signal processing
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architectures for science Developing and advancing extreme-scale scientific data management, analysis, and visualization Developing and advancing next-generation machine learning, AI, and data science approaches
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have a postgraduate degree, ideally a doctoral degree, in a relevant field and experience in computer-based analyses and presentation of experimental data. The successful applicant would have a proven
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the term of their appointment. In addition to annual leave, the Fellow may apply for leave to undertake research and fieldwork overseas, subject to the approval of the CIL Director. Application Procedure
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degree of 300 ECTS. In order to gain admission to the programme, the candidate must document sufficient potential for research. The applicant must have a grade point average of C (strong 3.0) or better
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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This is a theoretical/computational postdoctoral position for the prediction and development of point defects in two-dimensional materials for applications in quantum technologies. Project