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planning. b) Have knowledge of statistical computing, data science, data modelling, or data visualisation languages and software (e.g., PowerBI, Python, R, SAS, SPSS, SQL, Tableau, etc.) c) Have experience
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, and machine learning. Expert skills with at least one data analysis environment (e.g., R, Stata or SAS). Skills in machine learning and programming proficiency in languages like JavaScript and Python
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3 years postdoctoral experience). Proficient coding skills in at least one of Matlab, R and Python. Experience working with remote sensing. Experience with crop physiology is a plus. Strong numerical
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or adaptive designs. • Proficiency in at least one of the following: R, Python, JavaScript, or other relevant data analysis or app development tools. • Familiarity with EMA, EMI, MRTs, or SMART designs is
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functional interpretation of genetic variants. Proficiency in Python, R, or other bioinformatics languages. Knowledge of cloud computing, and high-performance computing (HPC) environments. Strong ability
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analysis (e.g., knowledge of Qualtrics, R, Python, etc., with strong statistical theory). An outstanding research record appropriate to the present stage of career, with evidence of potential for producing
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Intelligence, or a related discipline from a strong institution. Skills: - Proficient in programming languages such as Python, with experience in using AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn
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methods • Comfortable in mathematical modeling and analysis, including writing proofs • Proficiency in scripting in and performing data analysis in Python or Matlab • Research independence More
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constructive feedback, and strong organizational skills Passionate and clear about your own research interests Adept in running statistical analyses (e.g., Stata, R, SAS, MPlus) and/or in coding (e.g., Python
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components (low-noise amplifiers (LNAs), power amplifiers (PAs), mixers, oscillators etc) Experience in designing analog and mixed-signal circuits for RF applications. Knowledgeable in python programming, AI