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Field
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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photoelectrochemical ammonia synthesis funded by the Australian Research Council The successful candidate should have research experience in electrochemical technology and prototype design. They will have excellent oral
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., deep learning methods, multimodal AI) for the automatic identification of behavioral cues during ecological interactions with people and the environment and analyses of video and speech/language data
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involves building and training deep-learning models for TEM image reconstruction and interpretation, linking image features to local chemistry, defects, and dynamic transformations under varying
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. We are seeking a qualified Postdoctoral Research Fellow to join a team with international reputation for producing high quality research outcomes in the area of Inertial Confinement Fusion
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imaging, signal processing, or machine learning. Hands-on experience with ultrasound systems, particularly Verasonics platform is preferred. Familiar with programming languages and environments such as
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Postdoctoral Research Associate to join an Australian Research Council funded project led by Professor Kristian Ruming, titled "Student housing in (a time of) crisis: interrogating student housing supply". In
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Veterinary Medicine ● Variant discovery and genome annotation: Apply deep learning and graph-based models to improve variant calling, transcriptome annotation, and functional prediction in veterinary-relevant
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of computer graphics, human-computer interaction, computer vision, and machine learning. Conducting comprehensive literature reviews in related areas, including deep generative models, image and video synthesis
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establish independent research groups at FIMM and contribute to the development and application of cutting-edge statistical and machine learning methods in molecular medicine and population health. This group