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Field
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and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models 2. Hold at
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sequencing (NGS) and omics data analysis. Knowledge of microbial ecology, dysbiosis, and host-microbiome interactions. Familiarity with cell culture techniques. R, Python, or other data science tools
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: The desired candidate demonstrates strong theoretical and methodological capacities as well as documented expertise in computational methods. Documented experience with R or Python programming is also very
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evidenced in relevant publication(s) Proficiency in programming and data analysis in the statistical software environment R, Python, or other relevant programming languages, as evidenced in relevant
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) or cloud-based big-data pipelines. Experience with large-scale human genomic, omics, or brain imaging datasets. Strong programming skills in Python, R, or MATLAB, with emphasis on data analysis and AI model
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in Python, C++ or similar - particularly with an emphasis on high-performance computing Experience in crystal structure prediction or crystal growth prediction Experience in collaboration with project
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journal article(s) / GitHub). Excellent communication skills in English, both oral and written. Documented experience with scientific programming (e.g., Python, Matlab, R). You must meet the requirements
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gene identification (MEGARes, CARD, ResFinder). Proficiency in Python, R, or Perl, with experience in Linux/Unix environments. Solid understanding of antimicrobial resistance mechanisms, horizontal gene
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towards histopathology and spatial sequencing experiments. Extract RNA/ DNA from tissues and prepare sequencing libraries. Analyze spatial sequencing data using Python or R. Perform rodent neurosurgeries
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the statistical software environment R, Python, or other relevant programming languages, as evidenced in relevant publication(s) The following qualifications will count in the assessment of the applicants