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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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biology to tackle global biosustainability challenges. Learn more about our cutting-edge gas fermentation facility and platforms from: Valgepea et al. 2017, Cell Systems ; de Lima et al. 2022 Front Bioeng
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manipulation and spectroscopy. Problem-solving abilities, attention to detail, and the capacity to adapt to an evolving work environment. Demonstrated ability to learn new tools and applications quickly and
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, and willingness to contribute to a collaborative international environment are important. Good communication skills and fluency in English (both written and spoken) are expected. Application We look
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to work both independently and collaboratively in a research team. ● Excellent written and oral communication skills in English. Brief Description of Duties: The Postdoctoral Associate will assist
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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | about 21 hours ago
well as surface science techniques generally, is an advantage Readiness to learn and apply new experimental techniques Willingness to work in an interdisciplinary field and an international work environment Fluency
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through publications. Experience of analytical methods such as elemental analysis, spectroscopy (e.g. FTIR), chromatography or thermal analysis (e.g. DSC or calorimetry). Very good command of English
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, demonstrated through publications. Experience of characterising cellulose or fibrous materials, e.g. structure, crystallinity and purity. Very good command of English, spoken and written, as it is required in
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or sorption). Very good command of English, spoken and written, as it is required in the daily work. As a person you are independent, take initiative and have a strong ability to collaborate in
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. The postdoctoral researcher(s) will join an international research environment at Umeå University, including Stat4Reg (www.stat4reg.se ), which develops statistical and machine-learning methods for register data