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resistance mechanisms to targeted, chemo, or immunotherapies. Our long-term vision is to identify new therapeutic vulnerabilities, improve patient stratification and provide spatial proteomics data
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. This program offers a rare opportunity to combine methodological independence in artificial intelligence and biology with direct access to real-world clinical and translational research data, addressing global
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and industrial partners, and participation in project meetings and dissemination activities Is Your profile described below? Are you our future colleague? Apply now! Education PhD in Materials Science
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, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer
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and field monitoring work performed by a PhD student at LIST and other researchers in LAFI, and extend the existing Vegetation Optimality Model (VOM, https://vom.readthedocs.io ) to test the following
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project aimed at advancing our single-cell ribosome profiling technologies in cancer. For further information about the lab, please visit https://www.sendoellab.org/. The Institute for Regenerative Medicine
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Qualifications PhD in Neuroscience or other related field Experience in in vivo dosing (IV,IP, SC), mouse brain stereotactic surgery, in vivo two photon imaging, image analysis Qualified applicants must be
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Computer Science, with specialization on applied machine learning, statistical methods, and/or autonomous systems Strong programming skills Strong analytical skills Industry experience in information and
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intended to be all-inclusive and may be expanded to include other duties or responsibilities as necessary. CORE QUALIFICATIONS Education: PhD, MD, or equivalent degree in a biomedical field Certification and
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), carbon (C), and water between the biosphere, atmosphere, and hydrosphere from the landscape to the national level. Using a combination of state-of-the-art biogeochemical modeling, remote sensing, and data