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University Assistant (all genders) - Phd Position 40 hours/week | limited to 4 years TU Wien is Austria's largest institution of research and higher education in the fields of technology and natural
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neuroinflammation. The PhD student will help uncover the molecular and cellular pathways linking the allergic gut to the inflamed brain, and how these pathways shape disease risk later in life. The successful
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limited to: learning technology, information, language, and computing technologies to advance learning, training, cognitive development, and human performance. Position Overview Provides ongoing mentorship
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review or select your application. Knowledge/Skills/Abilities: Sufficient relevant experience to contribute significantly to a specific project. Experience with the use of computers and other appropriate
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College of Engineering and Computing (MCEC) by delivering research administration services to the MCEC Office of Research. This role is responsible for assisting faculty with building grant proposals
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The University of Vienna, Faculty of Chemistry, is home to the Vienna Doctoral School in Chemistry (DoSChem), Austria’s largest doctoral training program in chemistry and related sciences. Bringing
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The Mentor Doctoral program is an EU-funded Marie Skłodowska-Curie Action (MSCA) to foster and train Doctoral Candidates (DC) on the metabolic control of cell growth by mTOR in pathophysiology
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European collaboration State-of-the-art research facilities A dedicated training program to broaden your expertise and enhance your skill setA doctoral scholarship for a period of one year, with
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training program consisting of 23 academic and non-academic partners from 8 EU countries (The Netherlands, Belgium, Germany, France, Spain, Italy, Czech Republic, United Kingdom). MIRACLE aims to train 10
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PhD candidate in the automated detection of measurable residual disease in hematological malignancie
The Saeys lab at the Inflammation Research Center (VIB), Ghent, Belgium, is offering an exciting PhD student position focused on the development of a computational cytometry detection method