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(e.g., Python, C#, or Ruby) and platforms commonly used in digital forensics and backend development. Familiarity with software development lifecycle including design and documentation of software
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Canada, the USA, the UK, or New Zealand. Proficiency in Python, MATLAB, or C++, and demonstrated experience in deep neural networks and mathematical optimisation, are essential. A commitment to equity
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Matlab, Python, C++ or other relevant language and experience in deep neural networks. Experience and demonstrable expert knowledge in one or more or the following areas: deep learning; graph neural
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(i.e. python, R) and toolchain (i.e. PyTorch, Tensorflow, Scikit learn, CARET) Experience translating research code into production code is a strongly desired bonus An understanding of how systems
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publications, commensurate to opportunity. Demonstrated proficiency in Python, including data handling and backend development. Demonstrated experience developing applications interfacing with machine learning
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ideas. To develop algorithms, machine learning models, Python modules, demonstrators and training pipelines for publication and translation into commercial products that can be widely and reliably adopted
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management and programming languages such as R and Python. Level B Essential Criteria: A PhD in entomology or a related discipline, with at least 3 years of postdoctoral experience. A strong track record in
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analytical chemistry, particularly GC-MS analysis of trace volatiles Good communication and problem-solving skills Knowledge in data analytics (python or R) is desirable Knowledge in atmospheric chemistry is
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methods. Strong experience with scientific computing and data analysis, ideally using python or an equivalent language. A strong record of producing peer reviewed research-based publications in areas
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such as for example Superconducting Quantum Interferometers and Cavity Magnonics Interferometers. Ability to maintain and develop tools for more advanced experiments by using Python, MATLAB, COMSOL and