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one or more relevant programming languages/tools (OpenFOAM, C, Python, Git). PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application
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: Ability and motivation to conduct fieldwork in alpine environments, and willingness to obtain a UAV license. Interest in coding (e.g., Python, Matlab, R) and numerical modelling. Enthusiasms for working
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Science; Have knowledge of SQL, Python, ArcGIS, Power BI, Java, and SAS. Work plan and goals to achieve The work focuses on developing an Integrated Analytical Platform for Territorial Intelligence – Smart
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(or equivalent) in Computer Science, Statistics, Ecology, Biology or Forestry. · Documented experience with application of deep learning and advanced statistical analysis and programming (e.g., R or Python
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R and/or python. Familiarity with biodiversity assessments, aquatic ecology, boreal forest ecology, and forest management. Ability to work both independently and in collaborative teams. Field work
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PhD Candidate on The Future of Mixed Methods Research /Junior Lecturer in Methodology and Statistics
are appreciated but not required. Good research skills evidenced by good grades for research methods courses. Excellent data analytical skills, as evidenced by a good command of R and/or Python Experience with
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communication skills and the ability to thrive in interdisciplinary collaborations Basic programming or data science skills (e.g., R or Python) and an interest in omics data analysis are considered an asset We
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monitoring. Familiarity with tools such as Python, MATLAB, or embedded C would be advantageous. Most importantly, this project is ideal for applicants who are motivated to tackle real-world reliability
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, the candidate should have solid programming skills (e.g. Python, Julia) and an excellent command of English. You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level
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familiar with geoprocessing using Python Good theoretical understanding and practical experience using quantitative methods (including projections based on time series data). Good oral and written