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technology. Biofilm-based bioreactor design, construction and operation. Biofiom characterization and knowledge of DNA sequencing. Solid knowledge on standard methods for wastewater characterization
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have expertise in at least one of the following research areas: PDEs, numerical methods, optimization, functional analysis, or stochastic analysis Candidates without a master’s degree have until 1st
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assimilation to calibrate the coupled CLM-FATES model using: Snow cover Flux tower data The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model
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-use ropes in aquaculture, exploring their usage patterns, methods to reduce their consumption, and the implementation of biodegradable alternatives. The project work will involve field experiments
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or numerical methods in the context of environmental research is highly advantageous. Experience with the interpretation of field data is advantageous. Grade requirements: The norm is as follows: the average
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before 01.08.2025. It is a condition of employment that the master's degree has been awarded. Experience working with intermediate to advanced remote sensing data and methods is a requirement regardless of
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of the following areas is an advantage: Quantum sensing Hands on experience with nano fabrication and nano characterization methods Personal and relational qualities will be emphasized. Research experience
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techniques, different histological methods and advanced imaging. Contact For further information about the position, please contact Associate professor Anett Kristin Larsen : phone: +47 77 62 52 12 e-mail
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academic achievements in previous studies. Demonstrated knowledge of statistics and causal inference methods / econometrics, including good results in advanced courses. Experience with programming and
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have an excellent infrastructure covering chemical, structural, optical and electrical characterization methods. Part of the research will be conducted at the Micro- and Nanotechnology Laboratory , with