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: Education: PhD within the field of electrochemistry. Knowledge andProfessional Experience: Experience in electrocatalysis and scanning tunnelling microscopy (STM) Relevant publications within STM and
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: PhD within the field of electrochemistry Knowledge and Professional Experience: Experience in electrocatalysis, electrochemical alkane conversion and in situ spectroscopy with relevant publications
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of PhDs, and undergraduate students (thesis defence, students follow up, etc) · Tracking of the activities of the AEMD Group (team members, thesis, publications, group activities, patents, and
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, participation in project meetings, and rigorous management of data storage and analysis. Requirements: Education: A PhD in Biochemistry and Biology, Nanoscience and Nanotechnology, Materials Science or similar
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: Education: ·PhD in chemistry, biochemistry. Master in similar fields will be positivitely valorated. Knowledge and experience: ·Background in biosensor devices and clinical applications ·Knowledge in
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benchmarking. Contribution to SIESTA training events. Contribution to other activities in the group. Requirements: PhD in Physics, Materials Science, Chemistry, Computer Science, or related disciplines
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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural
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. Requirements: Minimum: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related field. Demonstrated experience implementing heuristic/metaheuristic optimisation (e.g
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. Requirements: Minimum: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related field. Demonstrated experience implementing heuristic/metaheuristic optimisation (e.g
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internal reports and manuscripts. Requirements: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge of machine learning, including graph neural