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techniques. Training or demonstrated experience in remote sensing, spatial data collection, and thematic mapping. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with
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., MatLab, Python, Modelica, C, ForTran, etc. We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
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transport measurements Familiarity with the theory of magnetism Proficiency in MATLAB/Python and LabVIEW for data acquisition and analysis Good written and oral communication skills Ability to work
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. Python, MATLAB, or similar) for data processing and data handling Experience with data processing, analysis and interpretation Excellent interdisciplinary communication – Strong collaborative skills
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their analytical work with numerical simulations coded e.g. in Python, and present their work in written notes and manuscripts, as well as give presentations to the project team and external stakeholders
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* Experience in one or more of: AAV/vector biology, in vivo gene delivery, mouse models/surgery, single-cell/spatial transcriptomics, ATAC-seq, microscopy, quantitative imaging, computational analysis (R/Python
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interventions. Candidates need to be able to understand statistical modelling, have a mathematical background, and be fluent in R programming. We will also consider candidates who have extensive C++ or Python
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skills (e.g., Python or C++) are advantageous. Experience with robotics, automation systems, bioprinting, or liquid handling platforms is highly preferred. Ability to work independently and develop robust
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measurements, awareness of noise, efficiency, and timing trade-offs in low-light imaging. Applicants should have competence in data acquisition/analysis and scripting for instrument control (e.g., Python/Matlab
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, or other high-dimensional omics datasets. Proficiency in R and/or Python, and familiarity with tools such as Seurat, Scanpy, DESeq2, edgeR, Monocle, or similar frameworks. Experience working with large-scale