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publication track record in relevant areas of high-energy astrophysics in leading academic journals. A strong interest in and commitment to the delivery of quality undergraduate education. Experience in and/or
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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programs. Demonstrated track record as a successful team player in the areas of administration, research, and teaching. Demonstrated delivery of innovative teaching and learning methods (including blended
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field. They will possess a demonstrated track record of high-quality research, including publications in leading journals and conferences, particularly in the area of electrode/electrolyte interface
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successful you will need: Proven track record in leading and modeling high quality teaching and learning practices in classrooms and supporting professional conversations with teachers. Familiarity and
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, with the successful applicant joining growing team that is committed to supporting research, teaching, and public debate in education. To be successful you will need: Proven track record in leading
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meet deadlines, with flexibility to alter priorities to meet changing demands. An emerging research track record with evidence of recent high quality scholarly publications. Demonstrated capacity to work
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AI/ML for Object Tracking and Sensor Fusion, you will develop next-generation algorithms that power intelligent aerial systems—enabling real-time object tracking, multi-sensor data fusion, and
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skills in R and Python. Demonstrated experience with the handling and maintenance of crops in field-based and controlled environments, and genetic transformation of cereal crops. A strong track record of
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proven track record as a reliable and trusted team player. They can conduct research and engage with stakeholders to build effective working relationships. They are able to comply with obligations