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. For both positions we expect: A strong background in thermodynamics, fluid mechanics, and heat transfer. Solid scientific programming skills, for example in Python or MATLAB. A documented publication
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methods is a plus Programming experience in MATLAB and/or Python Familiarity with process simulation software such as Aspen Plus or Aspen HYSYS Application and Selection: The application folder must contain
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ecosystems, forested wetlands, or peatlands. ● Demonstrated proficiency with statistical computing (e.g., R, Python) and spatial analysis software (e.g., ArcGIS, QGIS). ● Experience with carbon stock
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/Qualifications Strong research track record in AI and scientific applications. Excellent knowledge of Machine Learning and Deep Learning. Strong Python programming skills. Experience with PyTorch, TensorFlow
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-structured interviews (e.g., SCID). Knowledge/proficiency with statistical software (e.g., SPSS, SAS, STATA, MatLab, Python), and database management (e.g., developing databases in REDCap, Microsoft Excel
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experimental work in chemical or process engineering (desirable) Knowledge of process optimization, parameter estimation, or control methods is a plus Programming experience in MATLAB and/or Python Familiarity
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practical knowledge of statistical and programming packages is mandatory, including R, Python, and/or SQL. Extensive experience with advanced statistical techniques and algorithms, such as Machine Learning
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), obtained less than 5 years ago. Other Qualifying Skills and Abilities: Familiarity and experience with R and Python programming is essential. Experience in the analysis of next-generation sequencing data is
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for BB84, entanglement-based QKD and of free-space optical (FSO) communication Programming and instrument-control skills: e.g. Python, MATLAB, LabVIEW, for experiment automation, data acquisition and
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or program datasets. Proficiency in statistical programming and data analysis tools: R, Python, Stata, or SAS SQL/database management preferred. Ability to clean, harmonize, and analyze complex datasets from