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– Adsorption and reaction of small gaseous non-metal oxides on model mineral particles under light illumination. The position is for four years of doctoral studies, including participation in research and
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an increased interest in adapting and developing the latest machine learning methods for the purpose of malware detection, and preliminary results are encouraging. The specific goals of this project include
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, among other things, how the production of cement-based materials is affected by electrified processes that reduce carbon dioxide emissions, how trace elements such as rare earth metals are bound in
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the flexibility of neural methods. If successful, the work has the potential to advance applications such as automated theorem proving, knowledge-graph inference, and causal analysis. The Department of Computing
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formulation, purpose, and research questions Previous research and contribution to the research front Theoretical framework Research strategy, method, and material A cover letter summarizing your qualifications
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diagnostic methods, and applications to real datasets where non-stationarity and evolving dynamics play an important role. Qualifications The doctoral student will be admitted to doctoral studies in
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algorithms and methods for calibrated Bayesian federated learning for trustworthy collaborative Bayesian learning on data from multiple participants. The project will develop new methods, theory, and
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orientation, quantitative approaches and survey analyses may also be relevant alongside qualitative methods. The employment Positions as doctoral students in the doctoral program amount to four years of full
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the position Bioinformatic methods for single-cell metagenomic analysis Single-cell metagenomic sequencing (scMetaG) can provide maximum-resolution insights into complex microbial communities. However
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with big datasets: towards methods yielding valid statistical conclusions” led by Professor Xavier de Luna and Tetiana Gorbach (Statistics). The overall purpose of the project is to develop novel methods