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Field
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-life conditions; You will perform structure-property correlations and unravel the physical and chemical characteristics that determine the functional properties of the materials; You will collaborate
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geologically-informed screening techniques and performance criteria that enable us to quickly assess rank and identify the most promising fields for cyclic hydrogen storage such that they can be assessed in more
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generative model. As such, GenIR models are able to more deeply interact with the underlying corpus, enabling enhanced reasoning, adaptability, and performance in real-world scenarios. The position is embedded
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large genomics data and later incorporating the testing on known unwanted linkages. You will primarily be responsible for building a machine learning model and performing computational genomics
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hydrogen recovery given the different depletion states of the reservoirs. The ultimate aim is to develop a set of geologically-informed screening techniques and performance criteria that enable us to quickly
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of stochastic programming problems used in power system operations under uncertainty in conjunction with classical high-performance computing. Interesting directions for this project include, but are not limited
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in a 36-hour per week contract and receive an appointment for a duration of two years. Extension is possible with good performance. Our offer Driven by health; that's our mission. This applies not only
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perform a prospective trial at the Dutch Breast Cancer Screening Program to determine the impact on screening performance when optimizing the radiologist’s interpretation. This trial will involve two
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. Explore multiple surface modification strategies including Poly-L-lysine, silane-based approaches, and novel functionalization techniques. Molecular Recognition Elements: Characterize the performance
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: Characterize the performance of various receptors, ranging from Aptamers to Molecularly Imprinted Polymers (MIPs), optimized for specificity, affinity, binding characteristics, and photonic chip integration