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instruction. Preferred Education / Experience PhD and/or MD/DO preferred such as Biomedical Sciences, Physiology, Pathology, Molecular and Cellular Biology, or related field is required, as is the flexibility
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of lung cancer genomics, transcriptomics, and molecular biology. The successful candidate will join a young, dynamic, and interdisciplinary team dedicated to uncovering the molecular mechanisms driving lung
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), which establishes and maintains transcriptionally silent chromatin states. This PhD project aims to investigate how structural and biochemical features of these Polycomb proteins determine their
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position (contract-based) and one PhD fellowship in Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys). The PhD position is focused on efficient algorithms
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international partners to develop evidence-based solutions that inform policy and advance public health in Singapore and the region. SSHSPH provides a dynamic, interdisciplinary environment that supports
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physiology and biotechnology, cell and molecular biology, immunology, cancer biology. The program offers a dynamic and internationally competitive research environment with state-of-the-art research
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University of Jena - Cluster of Excellence "Balance of the Microverse" | Jena, Th ringen | Germany | about 14 hours ago
medical fields to enhance our understanding of microbial balance from the molecular to the ecosystem level. We develop tools and detection technologies to shape microbiome dynamics for environmental and
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the research team. Applying for research grants Qualification and personal qualities The applicant must hold a Norwegian PhD or equivalent doctoral degree in molecular and cell biology, and neurochemistry
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, Qualifications and Training : PhD in Solid-state Chemistry or Physics (or very close to completion) Experience in areas including (but not limited to) : Ionic conductors Dynamic properties of solids Advanced
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular