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We are looking for a talented and enthusiastic candidate for a fully funded 4-year PhD position. The PhD candidate for this project will be working at the RNA Structural Ensemble Dynamics group led
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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essential to accurately predict their snow performance in the laboratory phase. This enables the proper selection of the most promising candidates for tire prototyping, which will later undergo outdoor
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Your job As PhD candidate, you will be part of the project SHIELT – Shelf-life for plant-based meat alternatives. This project aims to develop predictive microbiology and risk assessment tools
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advanced operational strategies, such as model-predictive control, tailored to dynamic prosumer energy demand. Foster collaboration: Work closely with industrial and research partners, including CENAERO
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often inaccurate and costly. This process is long, expensive, and high-risk, with animal testing traditionally used to predict efficacy and safety for humans. However, animal experiments often fail
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that the viruses use the same frequencies of building block pairs as the host. Based on his data, it is now easier to predict after a general screening whether a virus found in a mosquito is dangerous to mammals
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augmentation for soil and biomass carbon forecasts and scenario modelling across Europe; developing and benchmarking uncertainty quantification methods for space-time predictions and for spatial blocks
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New LHC Triggers’, which is funded by the Dutch Research Council (NWO). The main goal of this project is to develop theory predictions and new searches for dark matter bound states in the ATLAS
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New LHC Triggers’, which is funded by the Dutch Research Council (NWO). The main goal of this project is to develop theory predictions and new searches for dark matter bound states in the ATLAS