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Field
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helpful, as is comfort with multi-omics (scRNA-seq/spatial, proteomics/metabolomics) and analysis in R or Python. A translational mindset—thinking in terms of potency, QC, and GMP-relevant considerations
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in C++ programming; - Knowledge of version control tools (Git). Minimum requirements: - Proven experience in C++ and/or Python programming; - Experience in developing graphical interfaces in a business
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of 20; Experience in python. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC), based
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systems or environmental sensing technologies. Strong programming skills in Python, MATLAB, or similar for real-time data processing. Demonstrated ability to work in collaborative, multidisciplinary teams
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-based proteomics data (DDA/DIA) Familiarity with software frameworks such as DIA-NN, FragPipe, or comparable platforms Strong programming skills in Python and/or R, and solid understanding of statistical
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Experience in Linux and computational languages including R, and Perl or Python Experience in AI/ML modeling Knowledge of genetics, next-generation sequencing, genome assembly and annotation Strong oral and
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tools such as SPM, FSL, AFNI, and/or DSIStudio etc will be an advantage. Signal processing and programming skills (e.g. with Matlab, Python) will be an advantage. Ability to use statistical packages
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computational statistics or machine learning is optional but highly relevant) ● Proficiency in programming languages (R, Python, C++, Java or Julia). ● Experience with mathematical and statistical methods applied
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projects. o Strong proficiency in data science and programming (Python preferred; experience with pandas, NumPy, scikit-learn; SQL). o Practical experience with ontologies/knowledge graphs (RDF/OWL
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background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software development, including Python, model integration, and system