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, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS
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. Desirable Demonstrated knowledge/experience in: multiphase flow porous media flow microfluidic fabrication and experiments 3D printing surface chemistry Demonstrated programming skills in: Matlab C++ Python
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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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; b) Programming languages: C/C++, Python, etc.; c) Previous use of ROOT and GEANT applications is considered an advantage; d) Experience in analyzing large datasets is considered an advantage; e
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HBIGS Heidelberg Biosciences International Graduate School | Mannheim, Baden W rttemberg | Germany | 6 days ago
foundation, with proficiency in R and Python. We expect you to be fluent in English and be a compassionate team player. LanguagesENGLISHLevelExcellent Additional Information Selection process Please submit
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | about 9 hours ago
(e.g. PACT). Skills in data analysis (e.g. Python, MATLAB, ImageJ) will be considered an asset. Specific Requirements A scientific scholarship from the National Science Centre (NCN) may be awarded to a
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• Programming skills (e.g., Python, MATLAB, R) • Experience with AI/ML methods or power system modelling Conditional Offer The award of the PHAETHON PhD Studentship is strictly conditional upon the candidate’s
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explore concepts form several topical fields such as: - Acoustics and interfacial fluid mechanics - Advanced wavefront control in complex environments - Experimental instrumentation (Python
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, ELT/ETL pipelines, AI/ML, Unity and Unreal Engine development, shading, real-time simulation, immersive scientific visualisation, digital twin, C/C++, Python are desirable. Applications from both UK and
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g