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, computational mechanics). Evidence of scientific programming and good software/reproducibility practice (e.g., Python/MATLAB/C++ and/or established modelling platforms). Familiarity with asymptotic and multiscale
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bacterial systems.* Solid understanding of next-generation sequencing and core bacterial processes (replication, transcription and translation).* Experience analysing large biological datasets using Python
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interpret research datasets, drawing meaningful conclusions using appropriate statistical methods and scientific reasoning. Develop and optimize computational pipelines, scripts, and workflows using Python
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datasets using Python or R. Ability to work both independently and collaboratively, with strong organisation, attention to detail and communication skills. Clear motivation to apply interdisciplinary and
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management/administration processes Desirable Experience working with Drosophila, live calcium imaging, Matlab/Python programming and/or behaviour A good publication record in neuroscience. Further details
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approaches. Familiar with common scientific programming languages such as python, C++, or Fortran. Experience with high performance computing environments is welcome. Candidates who do not strictly meet these
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. Experience in process modelling and simulation (e.g., Aspen, Modelica, MATLAB, Python). Strong understanding of heat exchangers, thermal loops, and multi-physics systems. Experience in techno-economic analysis
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econometric skills and proficiency in statistical programming using software such as Stata, R, or Python. Experience with administrative data and knowledge of advanced techniques, including structural
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pipelines for genomic data analysis, and of programming languages such as R, Python, or Bash script is essential, as is experience of working with High Performance Computing. Time management skills
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, analytics, and software development, ideally using tools such as Python or similar platforms. Experience developing dashboards or visualisation platforms (e.g. Grafana, Power BI, or web-based frameworks