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Field
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systems as intelligent biomaterials and biosensors Assembling cells into multicellular structures and tissues (e.g. 3D printing of cells) Interfacing biomolecular systems with solid-state technology
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including the associated circular on the job structure for academic staff at Danish universities and the provisions for PhD fellows as described therein as well as the Protocol on PhD fellows signed by
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. To this end, we combine interdisciplinary research in molecular, structural, and cell biology as well as in physiology, biophysics, epi /genetics, (bio)informatics, and multimodal data analysis. Main goal
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, production and function of sperm, fertilisation, as well as early embryonic development – in both health and disease. To this end, we combine interdisciplinary research in molecular, structural, and cell
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of the testis, production and function of sperm, fertilisation, as well as early embryonic development – in both health and disease. To this end, we combine interdisciplinary research in molecular, structural
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 3 months ago
USNH Employees should apply within Workday through the Jobs Hub app The research position is within the broad area of biophysics, structural modeling, and molecular dynamics (MD) simulations
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complementary aspects of how electric fields and electrode-associated niches influence the structure, function, and stability of methanogenic microbial communities in bioelectrochemical reactors. Together
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exploring other ongoing research programs and activities at the institute beyond their thesis projects. The working language is English. PhD Program: Education component A structured doctoral education
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on the development of fault-related microstructures and associated changes in fluid chemistry (Farrell et al, 2025). These results will be complemented by field-based structural geology and petrographic studies
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in English Solid knowledge in finite element analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks