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appointment. Job duties Mentoring new PhD students in numerical computational projects. Conducting comprehensive literature reviews in machine learning for subsurface flow and well performance and supporting
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evidence to support the evaluation of AI and machine learning models. This may include investigating data-centric AI strategies, such as data quality assessment, annotation refinement, dataset curation, and
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contribute to the development and validation of computationally efficient motor-twin models for permanent magnet synchronous machines. The work will focus on machine modelling, parameter and state estimation
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking
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into the Computer-Aided Design and Finite Element Analysis software tools used by Navantia DURATION OF THE CONTRACT The contract will be indefinite, in accordance with applicable law. It is cautioned that the context
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component of this role is 20% to 25% of the role. Uses subject matter and best practices knowledge to perform lab and/or research-related duties and tasks. Works independently to assist with project design
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work schedules and teleworking options (if applicable per job). UMB is a public university and constituent institution of the University System of Maryland. All employees are expected to work primarily
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the fulfilment, cumulatively, of at least one of the following requirements: a) Have demonstrated experience in computer programming. 8.2. The decision of exclusion on absolute merit is notified to the candidates
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monitoring, sensing systems, instrumentation, or transportation infrastructure analytics. Experience working with data-driven technologies such as sensor networks, machine learning, or AI-enabled
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investigate the structure and function of Antarctic microbial communities involved in the degradation of organic matter in iron-rich marine sediments and, consequently, in elemental cycles within marine