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digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
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proficient in programming languages commonly used in genomics research (e.g. Python or R) and have experience in working with bioinformatics software. Good knowledge of English is necessary. The successful
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practices in different research communities; Teach lessons and workshops such as data processing and analysis using R or Python, tools and best practices for data management, computational best practices
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, Python, Bash, and other programming languages for data analysis and statistical modeling. Automated Workflows Experience: Proficient in using HPC, Git/GitHub, Nextflow, Snakemake, or Docker for efficient
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advanced statistical analysis Expertise in youth research is an asset Proficiency in data processing and analysis software (e.g. R, Stata, Python, SPSS) Proficient in at least two of the following languages
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tracking) Memory and/or trauma Coding skills (e.g., Matlab or Python) Strong interest in psychical and past-life memory research; prior experience not needed Established research and publication record
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, Statistics, Epidemiology or related disciplines Experience in handling longitudinal and birth-cohort datasets Extensive experience in quantitative research (Stata, R, Python, etc.) Fluent in English (speaking
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co-simulation platforms (e.g., TRNSYS-Python) Implement and test AI-enabled smart energy management strategies in real-world settings Conducting in situ measurements, including planning, setting up
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include: *Doctoral degree in economics or political science. *Academic experience in economic theory, game theory, and statistical analysis *Proficiency with relevant software, e.g. Python, R, and STATA
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analysis, and/or machine learning (e.g., Python, Scikit-learn, PyTorch, etc.) is also desired. A track record of publishing in peer-reviewed journals on related topics is also strongly preferred. Application