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to develop resilient coordination architectures for networks of autonomous maritime robots operating in complex and communication-constrained environments. The research will investigate how heterogeneous
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application programming interfaces (APIs), through rigorous simulations and proof-of-concept (PoC) trials. This position is ideal for a researcher with a passion for solving complex problems at the intersection
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of complex, multi-stakeholder initiatives. Ability to independently lead a significant area of work with multiple stakeholders and partners. Demonstrated ability to lead teams and work in a team, collaborate
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in mathematical modelling and Bayesian inference while learning from three collaborating chief investigators. You will also build your publication record and professional networks through seminars
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The Research Fellow will have opportunities to work with well-characterised clinical samples, state-of-the-art laboratory platforms, and an extensive network of local and international collaborators
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(TASC) program of the ARC Industrial Transformation Research Hub for Intelligent Contaminant-Sensing in Complex Environments (IC-SensE). The TASCprogram explores consumer and workforce adoption of sensor
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, biochemical, environmental, and other multi-omics data in interdisciplinary research Active participation in international scientific networks, research consortia, or European collaborative initiatives (e.g
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fractures can play a key role on production performance. One of the persisting challenges is to create complex 3D fracture networks and solve multiphase flow efficiently. None of the existing tools can
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for cell transplantation therapies in animal models of Alzheimer's disease, stroke, and epilepsy. To achieve this goal, the candidate will combine a gene network-based approach with a machine learning model
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on Artificial Neural Networks and Gaussian Process modelling, to accelerate processing optimisation. Consolidate experimental, techno‑economic, and sustainability data into robust technical evidence packages