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funded PhD positions, supervision by some of Europe’s leading researchers in this area, tailor-made career development plans, training in cutting-edge techniques, secondments, and collaborations with
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databases regarding the thermomechanical behaviour of refractory masonry in the context of steel ladles used in the metallurgical industry; Development and validation of finite element models, considering
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Description About the NeuroNanotech Doctoral Network NeuroNanotech is a doctoral network funded by the European Marie Skłodowska-Curie Actions (MSCA) that will train eleven researchers to tackle one
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work independently and develop your ideas. A close-knit community of colleagues to collaborate and grow with. A solid pension plan via ABP, company fitness schemes, and access to various university
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Analytical Food Chemistry at Technical University of Munich | Freising, Bayern | Germany | about 1 month ago
positions for Doctoral Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship –to develop and support implementation strategies
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high potential for progression. The aim of the project is to develop an innovative in vitro model enabling investigation of the (micro-)invasion process in DCIS and identification of molecular markers
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, technology development, and bioinformatics at VIB-UAntwerp Center for Molecular Neurology (https://cmn.sites.vib.be/ ), at VIB (https://vib.be/ ), and at UBirmingham (https://www.birmingham.ac.uk
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Additional information on beginning, duration and mode of study The starting date of the PhD project is flexible. The initial funding period is usually three years. Find out more at https://www.bgc-jena.mpg.de
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their personal skillset to the discovery, development, and commercial translation of new 3D nanoscale magnetic metamaterials. What You’ll Do in this Project Size, weight, and power: the future is small
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electronic structure methods for the above-described properties. In more details, this will require the development of an automated approach that allows identifying the excited-states across several levels