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on strategic planning can be used in research-led education within spatial planning. This work will lay the foundations for development of courses and program and will take place in close collaboration with
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the Global South - Lund University . The project aims to critically examine the rise of digital agriculture through carbon farming programs in the Global South, with a particular focus on African and Asian
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administrative staff, and doctoral students. The department has a large doctoral training programme and coordinates three international master’s programmes. It has a well-established reputation for its broad
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cluster is part of The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS), which is a national research program in Sweden. The vision of WASP-HS is to foster novel
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programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS) Demonstrated skills in handling and analysis of large datasets Consideration will also be given to good collaborative skills, drive
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, and is financed by SciLifeLab and the Wallenberg National Program for Data-Driven Life Science (DDLS) and the Wallenberg AI, Autonomous Systems and Software Program (WASP). Work tasks and
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the appointment decision is made. The ability to plan and carry out research of high quality, teaching skills. Profound knowledge of numerical methods for partial differential equations. Knowledge of uncertainty
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: Experience with femtosecond lasers, ultrafast optics and nonlinear optics Experience in high-order harmonic generation and attosecond physics Other skills, e.g. instrument programming, data analysis, vacuum
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of degree certificates Your doctoral thesis and 1–3 scientific publications (including a specification of your contribution as an author in co-authored works) A research plan presenting the proposed research
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, including stringent controls, method validation, and troubleshooting in high-variability biological samples. Strong quantitative competence and programming experience (Python and/or R/Matlab) for reproducible