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Field
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. Basic Qualifications An ideal candidate will have a PhD in computational biology/bioinformatics/statistics/CS or another quantitative field, as well as superb programming (Python, shell scripting) and
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Postdoctoral Fellow (two open positions) in the High Energy Neutrino Group in the School of Physics.
modeling and cross-section measurements, particularly within experiments such as SBND, DUNE, or ProtoDUNE. • Proficiency in scientific computing and software development (C++, Python, ROOT), with experience
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scientific software development. Proficiency in C/C++ and Python, with experience in HPC environments (e.g., MPI/OpenMP; GPU experience a plus). Record of peer-reviewed publications appropriate to career stage
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measurements, awareness of noise, efficiency, and timing trade-offs in low-light imaging. Applicants should have competence in data acquisition/analysis and scripting for instrument control (e.g., Python/Matlab
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ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication skills in English Desired qualifications: Publications in reputed journals and
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, vibration, and structural dynamics. Familiarity with signal processing and vibration/acoustic analysis techniques. Experience with data analysis using tools such as MATLAB, Python, or equivalent engineering
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to calculate your points for admission. Emphasis is also placed on your: expertise in software tools related to simulation/optimization of energy systems, and coding using a high-level language (e.g. Python
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). Demonstrated experience in signal processing, including signal detection, characterisation, or waveform analysis. Proficiency in scientific programming (Python or equivalent) and experience working with large
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of statistical theory and methods and core machine learning methods. Documented Python programming skills. Excellent skills in written and oral English. The candidate's research proposal must be closely connected
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, environmental sciences, geoinformatics, or a related discipline. Proficiency in advanced learning techniques and statistical modeling. Strong programming skills in languages like Python or R. Professional