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.). Proficiency in hard skills: optical thin-film simulation, micro/nano fabrication, optical path construction, data analysis, and programming (MATLAB/Python etc.). Competent in soft skills: independent problem
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are required. Experience in python, Fortran, C++ and parallel computing are a plus. 3. Good publication record in peer-reviewed journals for fluid mechanics. 4. A Ph.D. degree in relevant
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education and skills in R and Python programming, PCR, tissue culture, western blotting for proteins, confocal microscopy, and RNA-seq data analysis experience to assist with an ongoing NIH research project
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, or quantitative biomedical research Strong programming and data-analysis skills in MATLAB and/or Python Demonstrated ability to independently design experiments, troubleshoot complex technical problems, analyze
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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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design for mechanical components, electronic prototyping, and Python programming would be beneficial; Experience with embedded system development, particularly programming MSP430 microcontrollers in C, is
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Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in programming languages such as C and Python Proficiency in deep learning
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project, you will prepare tabular and time series datasets, implement Python-based forecasting and regression experiments, test AI-assisted workflow components, and prepare technical outputs for project
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priorities, and a genuine interest in supporting scientific research within a team environment. Knowledge of R or Python, experience of high-throughput proteomics and sample-handling automation, or experience
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quantitative data analysis. Strong programming skills in Python, including the development of reproducible data-analysis pipelines. Experience coordinating research or data-analysis tasks across projects. Strong