46 software-formal-method-phd positions at Swedish University of Agricultural Sciences
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lecturer, the candidate must hold a PhD in landscape architecture, soil science or in a related discipline with relevance to the subject of the employment. Good ability to communicate in English, both spoken
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biology, ecology, environmental science, or a related field. Merits include experience in aquatic ecology, molecular biology, eDNA analysis, method development, and data analysis. Strong written and verbal
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methods, technologies, and materials to reduce reliance on unsustainable practices and fossil fuel-based compounds as a response to societal requests for green alternatives that maintain high performance
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participating in projects that collect and utilize agronomic data from forages and crop rotations, and (3) writing scientific publications and grant applications. Qualifications: Required: A PhD degree in a
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systems, and the development of methods for agriculture and forestry. SLU offers a broad research portfolio that enables interdisciplinary collaborations. There are substantial opportunities for applied
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long-term experiments. Your profile The candidate must have a PhD degree in silviculture and/or forest management or a very similar subject. The candidate must have proven experience in data analysis and
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Climate change and human disturbances are placing increasing pressure on Europe's forests, demanding advanced methods for early detection and monitoring. We are seeking a research assistant to
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. Subject description The subject includes studies of formal and informal governance, politics as well as studies of processes of change in societal transitions concerning environmental and sustainability
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for employment as associate senior lecturer are candidates who hold a PhD or have equivalent academic qualifications. Priority will be given to candidates who have received a PhD or equivalent qualifications
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, fitting to the project plan. Your profile The candidate should have a PhD degree in natural resource economics or a similar subject. Proven experience in data analysis of markets related to natural