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Field
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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to date focus on just one layer, understanding what keeps AF going is challenging. This PhD project aims to bridge that gap by combining advanced machine learning tools with a new experimental protocol
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through publications and presentations at leading conferences. This project will be undertaken in collaboration with Dr Feras Dayoub of the Australian Institute for Machine Learning, and Advanced Systems
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 3 hours ago
and cell culture techniques are desired. The candidate is expected to work closely with an interdisciplinary research team and must be motivated to acquire new experimental skills. PROJECT DESCRIPTION
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reinforcement learning problems. We are looking for a profile with the motivation and drive needed for making a difference that matters. You must bring an open mindset and like to create results via collaboration
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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, government entities, industry partners, NGOs and citizens – to collaboratively make sustainable change. Through transdisciplinary action research, the consortium investigates conditions for collective learning
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that by combining electrospray deposition (ESD) with scanning tunnelling microscopy (STM) it is possible to deposit intact conjugated polymers in ultrahigh vacuum (UHV) and to acquire unprecedented sub
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HPC environments Good communication skills to interact with collaborators ranging from machine learning researchers to pathologists or medical students Knowledge of biology and medicine is a plus Highly
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Characterisation" "Data Science and Machine Learning in Materials" "Plastics Recycling and Circular Economy" Research theme: "Materials Characterisation" "Data Science and Machine Learning in Materials" "Plastics