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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
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written by humans and large language models. Months 5-6. Development of green algorithms for syntactic analysis of natural language using HPSG grammars Where to apply Website https://sede.udc.gal/services
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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environment to support agricultural decision making with advanced remote sensing and geospatial technologies. Responsibilities: Develops advanced Agro-geoinformatic algorithms for monitoring and predicting
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flexibility for the PhD researcher to develop their own research ideas, and that plans or topics may evolve based on advancements in academic literature or emerging opportunities. Nonetheless, the primary
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responsibilities (dependent on experience level of applicant) Develop and improve multi-temporal InSAR processing algorithms (e.g., time series analysis, phase unwrapping, noise mitigation, filtering, atmospheric
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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packages to estimate variance components and/or in R; a desire to further develop advanced computational, modelling and algorithmic research skills, and utilize these developments into practical breeding