299 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ"-"Univ"-"UNIV" positions at Monash University
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In this project, we aim to pioneer foundational models specifically designed for time series data—a critical step forward in handling vast and complex temporal datasets generated across domains like
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Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications
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Research Fellow - Data Scientist/Clinical Data Engineer Job No.: 690434 Location: 553 St Kilda Road Employment Type: Part-time, fraction (0.5) Duration: 12 month fixed-term appointment Remuneration
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Automating code generation, SQL query formulation, and data preprocessing pipelines is a crucial step toward intelligent and efficient software development. This project aims to leverage large
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Research Fellow – Data Science & Biological Chemistry Job No.: 691543 Location: Clayton campus Employment Type: Full-time Duration: 12-month fixed-term appointment Remuneration: $83,280 - $113,025
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Research Fellow, Data Science in Health Promotion Job No.: 687776 Location: Turning Point, 110 Church Street Richmond Employment Type: Part-time, fraction (0.6) Duration: 12-month fixed-term
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Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social
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This PhD project focuses on the design and evaluation of hybrid quantum–classical algorithms for large-scale data analytics and optimisation problems. The research will investigate how quantum
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-quality spectral data from wet-lab experiments is expensive and time-consuming. Furthermore, relying on a single spectral modality often leads to ambiguous generation, as different molecules can yield
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown