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Field
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code via differential testing)We focus on techniques that apply to real-world software systems. E.g., in the past, we have developed techniques that find and fix bugs in widely used Python, Java, C/C
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. • Demonstrated skills in bioinformatic and statistical analyses of microbiome and ecological data including sequencing data. • Analysis skills: write and execute code in R, Python, GitHub etc., high-performance
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open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you will contribute: in the application of the developed
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good knowledge of experimental research methods and statistics, experience with sta-tistical software (e.g. JASP, R)•Programming skills (e.g. in Matlab, Python/Psychopy and/or R) or willingness
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or Python. Working with the workstream Co-leads and wider research team, they will contribute to analyses, publications, reports and dissemination, as well as undertake administrative tasks and present
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(e.g. APMS) with software such as Stata, R, MPLUS, or Python. The successful candidate will contribute to publications, reports and dissemination activities, present findings at seminars, meetings and
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(at least in Python and C++); ideally strong hands-on experience with ROS2. Experience in AI development, especially with neural networks. Experience with standard software development tools (Git, CI/CD, IDEs
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measure leg-generated forces. Investigate relationships between neural activity, muscle properties, and joint movement. Code in MATLAB or Python for data analysis, modeling, and tracking tasks. Assist with
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technology experts work together to build a framework on open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you
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available here . Key Accountabilities Research Assistant / Research Associate Support development and documentation of Python-based Design Tool workflow for D-Suite Project Formulate and solve optimization