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++, maintained on github and configured via python. You will work with .root files and explore different event generators as well as machine learning tools and algorithms. The nature of LDMX as an international
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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develop new communication theory and signal processing algorithms. The goal will be to develop theory, algorithms, and network architectural concepts to deliver ubiquitous network services across the globe
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the mathematical foundations of these fields, e.g., designing innovative algorithms and control strategies, as well as the development of technical solutions to adapt these new methods to applications in the areas
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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at the Science for Life Laboratory in Stockholm, a centre for large-scale life-sciences. NRM has a close collaboration with nearby Stockholm University, which includes joint supervision of PhD students. NRM has
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110 PhD students. The Department of Oncology-Pathology is responsible for undergraduate courses in Pathology, Oncology and Forensic Medicine for medical students, as well as for Tumor biology courses
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with .root files and explore different event generators as well as machine learning tools and algorithms. The nature of LDMX as an international project will require you to work collaboratively in
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are: a PhD, or an international degree deemed equivalent to a PhD, within algebra; the PhD must have been awarded when the appointment decision is made; good ability to develop and conduct research of good
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several