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statistical software (e.g., R, Stata, SPSS, Python) • Expertise in quantitative analysis, with preferred skills in o Quasi-experimental evaluation techniques (e.g., Difference-in-difference, PSM) o Social
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Python and R programming languages for modeling complex biological data. Preferably experience with medical imaging analysis, particularly MRI data processing and interpretation. Keen interest in
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in high-quality journals. • Proficiency in programming and modelling tools (e.g., R, Python, C/C++, Julia). • Excellent quantitative and analytical skills, with experience handling complex datasets and
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commonly used in genetics and molecular epidemiology. Expertise in R, Python, bash is required. Strong communication (oral and written) and interpersonal skills, and experience working in a large research
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advantage. Solid understanding of algorithm-hardware co-design, especially for robotics or edge AI deployment. Strong programming skills in C, C++, and Python, with experience in deep learning frameworks
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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
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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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., MatLab, Python, Modelica, C, ForTran, etc. We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU