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and implementing vision processing algorithms that enable robust robot tracking and autonomy. The ideal candidate will possess hands-on experience designing, implementing, and deploying computer vision
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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gene gain/loss events, horizontal gene transfer, and functional diversification within gene families. You will apply statistical models and machine learning algorithms to identify associations between
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Bioinformatics and Computational Biology headed by Ivo Hofacker. Our team works on the development of algorithms and methods for problems in Computational Chemistry, Systems Chemistry, and Computational Biology
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algorithmic graph theory. The purpose of the role is to contribute to the project "Algorithmic meta-classifications for graph containment", working with Professor Matthew Johnson, Dr Barnaby Martin and
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fingerprint identification (RFFI) for Wi-Fi. You will design novel RFFI algorithms and further evaluate their performance using practical testbeds such as software-defined radio platforms. You should have a PhD
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fingerprint identification (RFFI) for Wi-Fi. You will design novel RFFI algorithms and further evaluate their performance using practical testbeds such as software-defined radio platforms. You should have a PhD
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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The Role Applications are invited for a Postdoctoral Research Associate in Computer Science with a particular emphasis on structural and algorithmic graph theory. The purpose of the role is to
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare