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of microrobotics and micromechatronics. https://www.okayama-u.ac.jp/user/mechatro/ [Work content and job description] Research that contributes to the advancement of the fields of microrobotics and micromechatronics
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from the date of hire, with strong possibility of renewal contingent on funding For more information, please see: Training Program in Mental Health Services and Policy Research| Health Care Policy
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. This is a non-tenure track renewable position. Positions are available contingent upon enrollment, funding, and departmental needs. Stipend rates per course. Application Materials Applicants should submit
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. This is a non-tenure track renewable position. Positions are available contingent upon enrollment, funding, and departmental needs. Stipend rates per course. Position is not benefits eligible. Application
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involvement in the UK National Clean Maritime Research Hub, with ongoing research (e.g. https://doi.org/10.1016/j.adapen.2025.100255 , https://doi.org/10.5957/jst/2025.10.1.258 , https://doi.org/10.5750
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. Emerging Leaders (https://research.ubc.ca/federal-research-chair-programs/canada-impact-emerging-leaders ) will receive research funding and institutional supports to advance transformative research in
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: − Candidates who, with the award of the current grant, including possible renewals, exceed a cumulative period of three years in this type of grant, whether consecutive or intermittent. − Candidates who obtained
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-degree-granting courses who have already benefited from a grant contract and who, with this grant assignment, including possible renewals, exceed a total accumulated period of two consecutive or non
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services provided by Aalto University. We strive to combine the best aspects of remote and in-person work, and we offer flexible working hours. Your workstation is located in the renewed and vibrant Otaniemi
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 10 days ago
: tyrex.inria.fr Relational learning has recently gained renewed momentum through the development of end-to-end deep learning approaches over relational databases. In this setting, relational tables are typically