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collaboration with IHL and an industry partner. where you will be part of the research team to develop and demonstrate Building-to-Grid Integration through Intelligent Optimization and Predictive Control at SIT’s
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into the same devices. The research project is part of a larger consortium, gathering world-class researchers in remote sensing with expertise ranging from estimation and optimization theory to hardware design
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for strain optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support sustainable biomanufacturing. (Bio)pharmaceuticals: Processing science and technology for bio- and
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is required to have a PhD in operations research, mathematics, computer science or a related area. Experience in discrete optimization, demonstrated by at least one publication, is essential. Strong
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discrete optimization, demonstrated by at least one publication, is essential. Strong familiarity with stochastic optimization methodology, particularly sample average approximations and two-stage stochastic
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theoretical basis for modelling functional biodiversity, based on eco-evolutionary optimality (EEO) theory. The PDRA will be explicitly responsible for statistical analysis of plant trait data and the
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an integrated model of plant carbon allocation, based on eco-evolutionary optimality theory. The PDRA will be explicitly responsible for designing an approach to evaluate and model carbon allocation to non
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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This is a Research Fellow post to support the NIHR funded programmes OPtimal Timing of Induction of labour to improve Maternal and perinatAL outcomes (OPTIMAL): An individual participant data meta
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. The research focus of our group is on parallel computing, supercomputing, and performance tuning and optimization of advanced applications. Our team currently consists of 10 scientific and 3 administrative