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working with high performance computers (e.g., parallelizing and distributing code). Experience in distributed data management and workflow systems. Preferred Competencies Ability to work independently and
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projects will work towards this goal. PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en
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programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or large-scale data centers
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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Description This PhD project bridges computational neuroscience and machine learning to study the mechanisms of active forgetting—or unlearning—through the lens of both biological and artificial systems
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algorithms and complexity theory, including in both well-established settings (e.g., sequential computation on a single machine and distributed/parallel computation on multiple machines) as well as emerging
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addition to a vibrant and highly competitive residency program with 25 positions, we offer 9 fellowships and participate in numerous graduate schools and the MD/PhD program of the CU School of Medicine. Our
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Bayesian approach (Lages, 2024). Techniques used: Computational modelling, Bayesian inference, sampling and simulation techniques, prior distributions and posterior predictive checks, model comparison
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Funded PhD studentships The successful candidate for each studentship will receive full funding for tuition and stipend, at UKRI standard levels. International candidates are encouraged to apply
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further studies as a PhD candidate. Additional programme cost: £500 Fugitive methane in Scotland: Plume mapping and isotopic characterisation using Cavity Ring-down Spectrometry (Dr Adrian Bass) Supervisor