348 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation"-"U.S" positions at Monash University
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research facility, and working in collaboration with both academic experts and the Australian Eating Disorders Research and Translation Centre , this role is critical in developing meaningful interventions
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Since the 1990s, researchers have known that commonly-used public-key cryptosystems (such as RSA and Diffie-Hellman systems) could be potentially broken using an efficient algorithm running on a
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The existing deep learning based time series classification (TSC) algorithms have some success in multivariate time series, their accuracy is not high when we apply them on brain EEG time series (65
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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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part in developing and evaluating neuroimaging-guided brain stimulation techniques. Situated within the vibrant Addiction and Impulsivity Research Lab , the position contributes to a global initiative
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will work as part of a larger research team on this project which includes multiple industry partners. The objective of the Actionable Data project is to develop and prove a reusable framework for
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Fellow. This role offers the chance to be at the forefront of innovation in chemical biology, with a focus on developing cutting-edge tools for molecular sensing and imaging. Under the guidance of Dr
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models (e.g. tumour progression, tumour-drug sensitivity, survivability) by integrating multiple and heterogeneous data with associative data mining and ensemble learning methods.
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often provide dietary advice based on the average responses of groups to specific foods, rather than considering individual glycemic responses. This project aims to develop an AI-driven, personalised
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comfortable managing a variety of responsibilities—from supporting patient recruitment activities, helping prepare ethics and governance documents to handling sensitive participant data. You're known for your