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Studies for the Promotion of Diversity and Inclusion (LOSPD) Program duration: 4 years No. of scholarships: 5 Coordinator: Prof. Luigi Maria Sicca Contact e-mail: lospd@ssmeridionale.it 7. Mathematical and
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developing robust and feasible mathematical models for differential privacy by investigating the data dynamics (IID and Non-IID) of distributed machine learning. Besides, trustworthiness is another major
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@rmit.edu.au Please send your CV to akram.hourani@rmit.edu.au Required Skills: Programming and simulation: strong experience in Python or MATLAB. Mathematical modelling: probability, optimization, or multi-agent
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) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms for microscopy image analysis problems (2D/3D/4D/5D
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knowledge of energy system modelling or climate modelling Good knowledge of deep learning, PDEs or mathematical/numerical optimization methods Enthusiasm for challenging problems and interdisciplinary
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join a vibrant, supportive research community (around 20-25 people involved in fluids modelling research). Collaborate with the Leonardo Centre for Tribology: Work with top researchers on experimental
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of the infrastructure, design and execution of large‑scale measurement campaigns, and development of data‑driven models for room acoustics and spatial‑audio. The specific research direction will be finalised after
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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Applied Thermodynamics, Transport Processes and Mathematical Modelling. The center has recently entered dynamically into Biorefinery Conversions research field. The focus of Biorefinery Conversions research