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will involve identifying, sourcing, and installing various sensing equipment in Rux’s in micropilot plant. The data from these sensors will be integrated into an existing platform composed of open-source
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of single-cell molecular data. Experience and expertise in ML/AI algorithms for analysis of single-cell genomic data Demonstrated capacity to work collaboratively with researchers across both dry and wet
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detectors (GWD), including the LIGO detectors. Current projects include the development of wavefront sensors and actuators for improved laser-beam mode control in GWD, including a new facility for full
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responsibilities will be to: conduct high-quality research in intelligent sensing and control for complex project environments develop and implement AI-based algorithms (e.g., GNNs, deep reinforcement learning
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techniques based on 3D sensor perception and deep learning to estimate forest tree structure from high-resolution drone-based LiDAR point clouds and imagery contribute to a world-leading large-scale forest
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of the algorithms developed in this project. About you The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance
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of the postdoctoral researcher will include: To work closely and proactively with Prof Anton van den Hengel to scope and develop research ideas. To develop algorithms, machine learning models, Python modules
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ideas. To develop algorithms, machine learning models, Python modules, demonstrators and training pipelines for publication and translation into commercial products that can be widely and reliably adopted
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the primary responsibility of performing metallomics studies including the preparation of responsive fluorescent sensors for application in biological studies. This project is funded by a grant from the Human