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Field
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into the enzyme-substrate interaction in the same set of enzymes. Further, there will be collaboration with a PhD student from NTNU working with similar analytical methods on another class of carbohydrate-active
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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analysis and analytical data analysis workflows, together with other team members Implementing AI-based microscopy image analysis software as python packages Developing algorithms to deploy machine learning
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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and the data analyses of mass spectrometry data. Attending a total of six months secondments to learn novel algorithms form improving fecal MP samples' taxonomic and functional characterization
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution
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untapped potential remains in extracting value from this data. This PhD will explore advanced analytics techniques, including machine learning, digital twin modelling, time series analysis, spectral analysis
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critical steps of gastrulation and early development. Creating iPSC lines with mutations in elements of the GAG biosynthetic machinery. Applying novel GAG analytical technologies to investigate how changes
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good project and time management skills enabling you to meet project deadlines good analytical, writing and presenting skills; fluent in English, both written and spoken and the willingness to learn
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the use of instrumental analytical methods such as HPLC-MS, GC-MS knowledge in the preparation of plant tissues for the extraction of natural substances experience in the application of molecular biological