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are software representations of physical assets, processes, or systems. They leverage real-time data to mirror the behaviour and characteristics of their physical counterparts, enabling predictive maintenance
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these methods across different crops to identify conserved patterns of stress resilience 4. Identify candidate genes associated with key agronomic traits related to resilience 5. Contribute to software and web
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
software studies, and it analyses how GenAI is interfaced (SP1), how GenAI creates new relations to archives (SP2), experiments with prototyping alternative interfaces to GenAI (SP3), and utilise artistic
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beamline and its experimental workflows Promote the SCS through outreach activities and engagement with academic and industrial partners across Scandinavia Collaborate with beamline scientists, software
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at least one of the following statistical software packages: SAS, STATA or R Curiosity, internal motivation, a positive attitude and a strong love of science and scientific research Fluency in spoken and
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environments. Experience with software such as R, Python, SPSS, Stata, Sawtooth, Qualtrics or similar tools will be considered an advantage. The successful candidate should have strong analytical skills, good
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spectrometry, omics, audio, or other high-dimensional structured data. Interest in open-source software development; we plan to release Python packages alongside the methods papers and value contributions
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. The role You will contribute to the design and implementation of the ABLE platform, including software development, possibly some hardware prototyping, and evaluation with users. A key focus will be
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analysis skills; advanced proficiency in Stata, R, or comparable statistical software; the ability to specify, evaluate, interpret, document, and justify statistical models; strong academic writing skills