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the intricate evolutionary trajectories of lung tumours across space and time. This work will unveil the key drivers of cancer progression, immune resistance mechanisms, and potential vulnerabilities within
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the unique nature of clinical medical data with low disease prevalence and difficulty obtaining ground truth data. Major regulatory science gaps include lack of methods for AI algorithm training with limited
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hospitals. PRIMARY DUTIES AND RESPONSIBILITIES: The qualified candidate will focus on developing new algorithms, including agentic artificial intelligence approaches, for the clinical integration
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the neural mechanisms underlying goal switching and behavioural strategy selection, linking algorithmic theories of behaviour to defined microcircuits and pathways. The position will employ a multidisciplinary
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genomes in over 800 patients) from pre-invasive through to primary and metastatic disease setting, in order to understand cancer evolutionary life histories with detailed clinical annotation. The co-primary
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applications. The project is highly multi-disciplinary, integrating algorithm development, engineering, physics, and biology components. Candidate do NOT need to have expertise in biology to apply. BIRTLab
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algorithms, clinical decision support systems, and population health management platforms. Evaluate emerging technologies in clinical informatics and provide strategic recommendations for their adoption within
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algorithms, clinical decision support systems, and population health management platforms. Evaluate emerging technologies in clinical informatics and provide strategic recommendations for their adoption within