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: (1) Investigation on the effect of piecewise linear approximation and boundary effects; (2) Design and realisation of SMILE setup adaptions for large polarisation converters; (3) Process development
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, career development possibilities and conference attendance. Regular social events and get-togethers round off the programme. Find further details at https://www.phd.tuebingen.mpg.de/11580/PhD-Programs
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. Programme duration 7 semesters Beginning Only for doctoral programmes: any time Application deadline Please see https://flores.unu.edu/en/education/phd-programme for current information. Tuition fees per
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about the ISSE Institute, please visit our website: https://www.isse.tu-clausthal.de Your responsibilities include: Research and development in the field of software engineering for dependable and safe
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independently, outstanding team skills, and organizational aptitude round out the ideal profile. We offer you a thorough induction into your area of responsibility a diverse range of training and development
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 7 hours ago
environment is provided to prepare students for the doctoral process and post-doctoral professional development through a compulsory curriculum of 30 ECTS. Doctoral students receive high quality supervision
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Days and Welcome Guide: https://go.fzj.de/welcome KNOWLEDGE & DEVELOPMENT: Your professional development is important to us – we support you specifically and individually e.g., through training and
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addition, you will contribute to self-government at the department and to the further development of degree programmes, and will be involved in academic continuing education. Last but not least, you will
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=26764 Postdoctoral Research Opportunity in Bioinformatics (m/f/d) RNA modification and 5′ Cap Analysis
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: Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic