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learning, materials characterisation or computational materials science. Previous experience with machine learning, computer vision, graph neural networks, Python, SEM/EBSD, XRD, image analysis
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Remuneration: $37,145 (tax-free RTP stipend) For scholarship procedures and conditions, please see: https://www.monash.edu/graduate-research/future-students/scholarships/scholarship-policy-and-procedures
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, data science, or related - Strong programming skills (Python and/or R) - Experience with machine learning or data analysis - Knowledge of deep learning frameworks Application Procedure Interested
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Python and/or Julia using LINUX-based OS. Communication of findings through journal publications, conference presentations and project reports. Candidate Requirements Applicants must satisfy the criteria
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status of northern Australia's remarkable lizard fauna under climate change, invasives and habitat loss. (Lab: https://www.chapplelab.com ) Why is genetic variation for fitness so high? (A/Prof. Tim
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, computer science or a related discipline. Experience with Python or another scientific programming language would be highly desirable. Prior experience with GNSS-IR or data assimilation is not essential, provided
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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Training Program (RTP) Stipend https://www.monash.edu/study/fees-scholarships/scholarships/find-a-scholarship/research-training-program-scholarship#scholarship-details . Be inspired, every day Drive your own
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e.g. Python/R. Desired experiences: Molecular laboratory, bacteriology and/or cultivation-based experimental work. Network-based analysis of multi-omics data. Molecular lab experience A PhD student with