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fellow researchers and industrial partners within the research area. For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree. Your immediate leader
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if you can document that you are exceptionally suited for a PhD education, for example through relevant work experience and/or peer-reviewed academic works. Excellent oral and written presentation skills
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We are now looking to appoint a PhD student in Ionic Thermoelectrics and Electrochemistry for Thermal Energy Harvesting, placed at the Department of Science and Technology, Campus Norrköping
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, a university (Monash University for this project) and CSIRO to co-develop a four-year industry-focussed PhD project. You will receive a four-year scholarship package of $48,071 annually (2026 rate) if
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Description Start date/duration 15.02.2027 for 4 years Job profile: Your responsibilities: PhD thesis in the field of Empirical Finance Independent research in the field of Empirical Finance Independent
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
, biotechnology, and additive manufacturing. As a PhD student, you will investigate fungal-bacterial interactions, develop living bio-composites based on microbial biomineralization, design bio-based hydrogel
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, see: General syllabus for the Board of the faculty of science and technology Further information Employment as a PhD student is limited to 4 years, teaching and other department duties may be added with
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doctoral programme in Technology within three months of starting in the position. (https://www.usn.no/english/research/postgraduate-studies-phd/our-phd-programmes/technology/). The doctoral programme
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standard simulation methods. This PhD topic falls within the area of computational materials science and will involve the use of established methods such as density functional theory and molecular dynamics
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and analysis of dedicated algorithms for training analog circuits directly from data. In this PhD project, you will develop a novel system-theoretic framework for learning in analog circuits and