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                , FEDER and FCT, is available under the following conditions: OBJECTIVES | FUNCTIONS Cloud computing is currently in an impasse. While hardware efficiency is improving at an exponentially lower rate, the 
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                (LLMs); Configure and optimize cloud computing solutions or on-premise infrastructures that ensure high availability and scalability; Implement tools for efficient resource management, such as GPU 
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                Professor at the Department of Informatics of the School of Engineering of the University of Minho and José Alberto Lencastre Freitas Borges de Araújo, Associate Professor at the Department of Curriculum 
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                is identified. For further information For a confidential discussion regarding this position, contact: Associate Professor Russell Brewer Deputy Dean, Research – Faculty of Arts, Business, Law 
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                environments, and compile findings and recommendations The work will be carried out at the Laboratory for Informatics and Systems of Instituto Pedro Nunes (LIS), under the scientific supervision of Professor 
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                ). Place of work: The work will be developed at the LASIGE – Computer Science and Engineering Research Centre, Faculty of Sciences of the University of Lisbon, under the scientific supervision of Professor 
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                cancer genomics and functional interpretation of genetic variants Proficiency in Python, R, or other bioinformatics languages Knowledge of cloud computing, and high-performance computing (HPC) environments 
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                information about the position, please contact Associate Professor Loïc Guégan : phone: +47 77646341 email: loic.guegan@uit.no For administrative questions, contact Martin Fjellvang Osima: phone: +47 77 64 62 
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                Associate Professor Duane Loh on conducting research at the interface of Machine Learning and Microscopy under a project on Learning Spatiotemporal Motifs In Complex Materials. The main responsibilities 
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                Associate Professor Duane Loh on conducting research at the interface of Machine Learning and Bio-imaging under a project on Learning Spatiotemporal Motifs In Complex Biological Systems. The main