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Willingness to combine wet-lab experimental work and computational analysis Basic knowledge of statistics and/or programming (R, Python, or similar) Strong motivation to learn new techniques across
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at Saxion University of Applied Sciences, you will contribute to the development of machine-learning models that connect powder characteristics and process parameters with the properties of the final
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Constructor Technology, invites applications for a PhD position in machine learning for software engineering and formal methods, on the Constructor Fabric project. Constructor Fabric turns a company's informal
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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projects, CEDLA coordinates education programs such as the BA Minor in Global Justice and the MA program Global Justice and Social Transformation. Through a community approach, the staff, postdocs, PhD and
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: procedural or node-based production, AI or machine learning, or technical art. Applicants should have demonstrable programming or scripting experience and the ability to develop and evaluate working software
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, and machine-learned force fields to describe ion transport and interfacial evolution. These models will be extended to mesoscopic and continuum scales (kinetic Monte Carlo, phase-field) to capture
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focus on combining simulations using spatial-genetic-demographic individual based models (e.g., using the software SLiM), machine learning approaches, and genomic data to estimate larval dispersal
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data and archaeological signatures (e.g., circular mounds, linear ditches, rectangular foundations, etc.) tailored for AI applications – Feature engineering and representation learning to enhance
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Fully Funded PhD Studentship (UK Students Only) Real-Time Sub-THz Electromagnetic Sensing and Machine Learning for Dynamic Particulate Characterization University of Birmingham with support from