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., Tacchetti, A., Bakker, M.A. et al. Scaffolding Cooperation in Human Groups with Deep Reinforcement Learning. Nat Hum Behav 7, 1787–1796 (2023). [22] Melnyk I., Mroueh Y ., Belgodere B., Rigotti M., Nitsure A
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characteristics of TMEs [1]. In lung cancer, several deep learning studies using Haematoxylin and Eosin (H&E) images have demonstrated that the spatial organisation of stromal and immune cell populations within
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both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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or implementing deep learning approaches on existing clinical systems). Experience and interest in grant writing would be viewed favourably. To be successful in this position, you will have: A PhD in a relevant
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collaborations in areas such as healthy living, transport, green energy, and advanced manufacturing. The role requires strong hands-on technical skills in modern AI, including deep learning, LLMs, Agentic AI, and
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individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fuelled by curiosity and a deep sense of responsibility
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PhD student position on development of innovative bifunctional oxygen electrodes for SOC technology.
development of innovative SOC stacks gathering deep knowledge on electrochemical and structural characterization of energy technologies such as fuel cells and electrolyzers. Among the characterization
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we lead in flexible work to enable an outcome focused and inclusive workplace. To learn more about our culture and hiring process, visit our Jobs at Macquarie page. Where to apply Website https
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Health Prevention: Investigate how LLMs associated with deep learning can be used to identify early signs of mental health disorders by analyzing digital diaries, questionnaires, voices features, physical