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of the most persistent challenges in modern software development: "flaky tests"—automated tests that pass and fail non-deterministically without changes to the code. In this role, you will bridge the gap
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Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8208F leave the ‘Research Area’ field blank select ‘PhD Energy Materials' as the programme of study You
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select ‘Create a Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8208F leave the ‘Research Area’ field blank
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MRC DiMeN Doctoral Training Partnership: Exciting PhD opportunity - Cracking the RNA Code of Inflammation: A New Frontier in Ageing Research
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data and operation of complex data base and information systems in order to code and abstract medical data and routine data entry. Record and code incoming forms etc, checking for inconsistencies
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or ROS 2 for real-robot software integration. Proficiency in Python and C++, with experience developing and maintaining production-level code. At least 2 years of experience in robotics research
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solutions, develop machine learning/AI pipelines and deploy these pipelines in production. You can demonstrate experience in programming languages (e.g., Python, R, C++), software engineering (e.g., coding
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Application’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8040F · select ‘PhD Civil Engineering – Water Resources (full time
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neutrino physics—using a combination of CMB and large-scale structure data. The analysis will rely on modified Boltzmann codes (e.g. CAMB or CLASS) and Monte Carlo techniques for parameter inference
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code: 8208F · leave the ‘Research Area’ field blank · select ‘PhD Energy Materials' as the programme of study You will then need to provide the following information in the ‘Further Details