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of computer-aided tools for chemical and biochemical product and process modeling, process synthesis, design, analysis and operation. The tools are applied in the chemical, petrochemical, pharmaceutical
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in developing and implementing project ideas. Is motivated to invest the effort required to publish in leading academic journals. Has excellent training in statistics and quantitative methods with
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an autonomous framework for setting up, executing, and optimizing complex electronic structure workflows, ranging from ground-state Density Functional Theory (DFT) to many-body perturbation theory methods such as
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collaboration with local water utilities and software developers Integrate digital urban water twins with data, applying methodologies for data assimilation, parameter estimation, and quantification of model
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performance. To investigate the ecophysiological consequences of an ice-free Arctic for marine fishes, the post-doc will estimate the field metabolic rates for a range of marine fish species using a novel
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to the discussions with the project partners (with reciprocal visits during the employment period) and work towards the project deliverables; explore new methods construct LRC codes from algebraic curves and/or
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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields
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(UCLA) as external collaborator. Brief project description The project develops new methods for causal inference when covariates are high-dimensional – settings in which traditional estimators often face
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Introduction MoPo investigates the role of moral judgment in contemporary politics, where citizens increasingly judge one another as good or bad people. While this moralization can reinforce democratic