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new models of examining the data To provide teaching to junior staff in the lab in neuroscience-related research methods, especially in pre-processing and processing of EEG data from infants/children
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-end technologies (e.g., Node.js, Python/Django/Flask, REST APIs, SQL/NoSQL databases) Demonstrated knowledge of AI/ML methods, such as supervised learning, NLP, or deep learning, with application
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missions will be implemented, while also increasing the number of elements in the formation when considering scenarios such as reconfigurations and position switching in low-Earth elliptical reference orbits
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with all members across each of the institute’s divisions. Candidates are expected to be highly familiar with: climate change and decarbonisation issues; and quantitative or qualitative analysis methods
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yeast and fungi for food ingredient and biochemical production. The specific goals are: 1. Metabolic engineering of Yarrowia and Candida yeasts for organic acid production 2. Design and optimization
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methods • Comfortable in mathematical modeling and analysis, including writing proofs • Proficiency in scripting in and performing data analysis in Python or Matlab • Research independence More
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using, or developing, the appropriate methods and/or techniques; Lead and promote activities designed to develop collaborative research with research colleagues and support staff internally and to
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fellows and other researchers. Strong interpersonal and written and verbal communication skills and ability to effectively train users and staff on proper procedures and methods for using advanced
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to the following: - Independently carry out the design and execution of experimental research required by the research component of the project. Independently analyse complex data sets. Write and review research
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to produce two journal articles during their contract. The successful candidate must demonstrate good competence in quantitative research methods and be proficient with statistical software such as STATA or R