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principled new models and methods, for modern machine learning problems. Machine learning recently has been largely advanced by differential equation-based frameworks, such as generative diffusion models
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, optimizing, and deploying AI models on HPC and GPU-based systems. Provide guidance on performance optimization, scaling, and efficient resource utilization. Contribute to architectural and design decisions in
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in AI and cybersecurity to develop novel solutions to cyber-resilient AI for the benefit of Swedish industry and society. The vision is to make Sweden a role model in secure trustworthy AI by
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development related to the above areas. Publications in first class journals and highly competitive conferences in areas relevant to the work, i.e. network modelling and protocol emulation in virtualised
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scaling model sizes, training budgets, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on
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-on workshops, bootcamps, hackathons and technical courses using HPC and AI infrastructure. Align training activities with MIMER’s compute services and expert support model. Ensure that training content is
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utilizing Python and web-stack technologies (such as JavaScript), to translate theoretical models into functional, testable software in close collaboration with our core research team. Beyond software
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look forward to receiving your application! If you have experience in research on canine behavioural biology and are skilled at analysing large datasets, this position may be the right fit for you! Work
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for efficient last-mile deliveries with a focus on climate and flexibility. Using advanced modeling and data analysis, you’ll create solutions that make final deliveries smarter and more sustainable. Your work
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AI challenges, particularly in life sciences, materials science, autonomous systems, climate research, or large-scale language models Experience from work in information security, in advise and