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at transforming pharmaceutical development and manufacturing. Candidates should have a doctoral degree in a relevant field, such as chemical or mechanical engineering, computer science, biomedical engineering, or a
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regeneration by integrating state-of-the-art omics approaches with genetic mouse models and human cell culture systems. Specifically, the postdoc will work on investigating molecular mechanisms of direct cardiac
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procedures to effectively utilize the facility for material testing. Analyze and interpret data collected from experiments, utilizing advanced computational methods and software. Mentorship and Training
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or Python) is required. Experience with large-scale concrete testing, modeling, and simulation (e.g., COMSOL, Abaqus) is a plus. Familiarity with AC impedance spectroscopy, electro-mechanical impedance, wave
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-Rei Yu. The postdoctoral fellow will be working in the area of immunology and pulmonary vascular diseases, studying the mechanisms involved in immune regulation of pulmonary vascular remodeling and the
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the VEGF pathway. However, challenges like adverse events, drug resistance, tumor recurrence, and lack of biomarkers limit their effectiveness. Further research into angiogenesis mechanisms, drug development
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to establish a distinctive, internationally recognized research and teaching program to address UM6P's challenges in research and education, particularly in green and environmental chemistry applied to all
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) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research activities and a wide-ranging portfolio of education programmes. Celebrating diversity and
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mechanics using wearable sensors. • Models of bone health in running populations. • Models of tissue stress and strain in athletes. • Models of health and performance in female athletes. • Models of athlete
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computational modeling of behavior to identify the underlying circuit computations. Current projects in our laboratory emphasize task-structured behavior assays, including set shifting, reversal learning