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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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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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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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toward green steel. To ensure that the steel produced by new processes is viable for industrial applications, it is crucial that these properties can be predicted with high precision. Position description
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of methane dynamics in rapidly changing ecosystems and contribute to improving predictive models of future methane emissions. Field sampling will focus on regions where methane cycling is still poorly
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change the ability of the ocean to absorb CO2 . The magnitude of this impact and the processes involved remain however difficult to predict. Also in the past, the strength of the AMOC varied and abrupt
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toward green steel. To ensure that the steel produced by new processes is viable for industrial applications, it is crucial that these properties can be predicted with high precision. Position description