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                Successful candidates have strong skills in computational molecular (bio)physics, structural biology and scientific computing, as well as a keen interest in interdisciplinary research and 
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                Description Thinking of doing your PhD in the Life Sciences? The International PhD Programme (IPP) Mainz is offering talented scientists the chance to work on cutting edge research projects 
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                physical analyses using XRD, XPS, SEM, TEM, and Gas sorption analyses Electrode integration and processing studies: Incorporate catalysts into planar electrodes and investigate processing effects to ensure 
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                Description Thinking of doing your PhD in the Life Sciences? The International PhD Programme (IPP) Mainz is offering talented scientists the chance to work on cutting edge research projects 
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                that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through 
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                semiconductor properties to the composition of lead-free double perovskites Your Profile: Master’s degree in theoretical or computational physics, chemistry, materials science, or a similar field Familiarity with 
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                Description The Graduate School Scholarship Program(GSSP) of the German Academic Exchange Service (DAAD) is offering two (2) doctoral scholarships for aspiring PhD students within the framework 
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                Description The Graduate School Scholarship Program(GSSP) of the German Academic Exchange Service (DAAD) is offering two (2) doctoral scholarships to earn a PhD within the framework of “Ancient 
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                Description Thinking of doing your PhD in the Life Sciences? The International PhD Programme (IPP) Mainz is offering talented scientists the chance to work on cutting edge research projects 
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                of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did