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, compression, learning, and inference for classical and quantum data exchanged through classical and quantum networks. The objective of the PhD study is to explore and address research and design challenges
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on purified CO₂ gas as feedstock, necessitating costly and energy-intensive capture, purification, and compression processes. Furthermore, high-efficiency alcohol production has primarily been demonstrated
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head-on. We will reinvent generative cooperative vision and semantic compression methods so fleets of intelligent machines can perceive the world robustly, efficiently, and in a trustworthy manner—even
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obesity. The matrices will support long-term cell culture in microfluidic systems to capture early tumorigenesis and will be functionalized with relevant tumor-promoting factors (e.g., pollutants, glucose
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features enhance binding to the receptors. This information will be carried forward to human tasting panels. You will also investigate how other components of food matrices inhibit binding. You will thus
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or 3-dimensional spaces, enabling insights about the underlying structure and distribution of the data. However, due to the heavy data compression into a space with only 2 or 3 degrees of freedom
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should demonstrate expertise in both qualitative and quantitative carbohydrate analysis, particularly within complex food matrices. The successful candidate will preferably have experience engaging
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sequences, analyse those data using Bayesian, Maximum Likelihood and coalescence approaches, and build matrices of geolocation and morphological data. The work will be alongside others working on related
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HPLC-MS, GC-MS experience in the extraction of natural compounds from complex matrices knowledge of the isolation and structural elucidation of natural products experience in the statistical analysis
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starlight. In ICE-EEVOLVE , we seek to unravel how chiral organic molecules, trapped in amorphous ice matrices, evolve from molecular clouds through star-forming regions to planetary systems. Laboratory