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Field
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processing or quantitative analysis tools (e.g., ImageJ, Python-based analysis) will be valued. Motivation to work at the intersection of experimental synthesis and data-driven materials optimization. Strong
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analysis (Excel / R / Python); Use of reference managers (Zotero, Mendeley, EndNote). Specific Requirements - Knowledge of water treatment processes, particularly Advanced Oxidation Processes (AOPs) and
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skills in Python and experience with deep learning frameworks such as PyTorch or TensorFlow, as well as familiarity with medical image analysis and computer vision. Experience in federated learning, AI
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with neuroimaging analysis software Strong quantitative and analytical skills, including experience with statistical software (e.g., R, Python, MATLAB). Excellent written and verbal communication skills
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trapping of biomolecules or cells, biochemistry and, microfluidic buffer handling techniques (preferred but not strictly required). Strong quantitative skills (signal processing, rheology models, Python
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programming (Python, matlab). Knowledge in printing/deposition techniques. Knowledge/experience in large scale deposition/printing techniques. Experience/Background in polymers science. Capability to work
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. Knowledge and Professional Experience: DFT-based methods. Scientific programming in Fortran, in MPI/OpenMP-parallelised codes. Knowledge of other languages (in particular python) and of GPU offloading will be
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: Demonstrable knowledge (advanced/expert level) in Bioinformatics and omics data analysis. Technical Skills: Advanced proficiency in programming languages essential for data analysis (such as R and/or Python
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programming (Python, MATLAB), neural networks, deep learning or physiological signal analysis. - Minimum of 2 years of accredited professional or research experience in tasks directly related to: AI algorithm
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/4590 Requirements Research FieldEngineering » Computer engineeringEducation LevelBachelor Degree or equivalent Skills/Qualifications Strong knowledge of C, C++, and Python (Rust is a plus). Experience