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Discipline: Engineering & Technology, Materials Science, Mechanical Engineering Qualification: Doctor of Philosophy in Engineering (PhD) This project is a collaborative research effort between
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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. However, there are significant challenges to a broad proof of concept that would be addressed in this PhD project. Laser beam sources, process development and control to enable better control of mass
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin
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Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission
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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and
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-periodic structures, we can precisely control the interaction of radiation with matter, potentially achieving unprecedented timing resolution (sub-70ps) and significantly enhancing signal detection. This PhD
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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advanced computational analysis of large-scale neural recordings. What you would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses