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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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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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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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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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(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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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
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, Matlab, Python or R) Demonstrated a high level of expertise in analysis of large and complex datasets Detail-oriented and excellent communication skills Excellent command of written and spoken English
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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
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knowledge of an interpreted language (Python, R, etc.), the knowledge of Netcdf format would be a plus, writing scientific articles (at least one publication as 1st author in a peer-reviewed journal