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project will focus on applied economic analysis of agriculture’s uptake of more sustainable production practices and practices to improve preparedness and resilience. The project will be predominantly based
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programming capabilities with ample experience from previous projects are a requirement. Strong experience with Python, data analysis, and visualisation techniques is a bonus. The results of this work will be
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qualifications and relevance of previous studies Experience with quantitative methods, modelling, data analysis and/or geoscientific techniques, as well as fieldwork experience Scientific motivation and research
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digitalization, digital technologies and media (e.g 3D modelling), and quantitative and qualitative scientific methods including those related to digital technology, media and advanced data analysis, will be
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, quantitative/qualitative methods including those related to digital technology and advanced data analysis, will be regarded favourably. Interest and/or familiarity with indigenous or minority communities
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Subject area: Applied economics Description of the doctoral project The research area is agricultural and food economics. This PhD project will focus on applied economic analysis of agriculture’s
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, data analysis and/or geoscientific techniques, as well as fieldwork experience Scientific motivation and research potential Ability to work independently and collaboratively in an interdisciplinary
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spectrometry, thermal analysis, mechanical testing) Your PhD research will contribute to the development of next-generation bio-based materials from forest resources. Within the GreenPolChem group and WWSC
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sciences; Have experience in programming and/or quantitative data analysis; A keen interest in working across scientific disciplines, including physics, chemistry and biology; Excellent interpersonal and
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concepts Structure–property relationships in bio-based materials Advanced characterization techniques (e.g. NMR, GPC/SEC, mass spectrometry, thermal analysis, mechanical testing) Your PhD research will