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Solutions (BISONS) Lab. Our research team aims to contribute toward finding solutions for sustainable futures that can benefit people and nature. We focus on developing new insights on human-nature
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the material requested: https://recruit.ap.uci.edu/JPF10271 Department: https://mbb.bio.uci.edu/ Qualifications Basic qualifications (required at time of application) Accepting all applicants. Application
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the United States using National Vital Statistics System (NVSS) mortality data. The candidate will be mentored by Drs. Noele Nelson, Corinna Noel, and Alistair Hayden, who will support the development of independent
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development of explainable and interpretable classical and quantum deep learning algorithms - Design and development of hackathons and other collaborative methodologies to promote the control of artificial
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Penn State (https://clima.psu.edu ). The position offers unique opportunities for research, education, outreach, stakeholder engagement, cross-disciplinary mentoring, and professional development. All
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developing leaders who are empowered to halt the climate crisis and create an environmentally sound future for generations to come. To learn more about SEAS and our values, please visit our website at https
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Albert Einstein College of Medicine (Bronx, NY) | New York City, New York | United States | 11 days ago
investigating how environmental exposures and inflammation drive hematopoietic stem cell dysfunction, clonal hematopoiesis, and the development of blood and prostate cancers. Our research bridges basic
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tools and methodologies into their teaching and research. This work will include: Offering one-on-one consultations, which may develop into longer-term research collaborations, including substantive and
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description ACT! is seeking a postdoc to develop practical tools for assessing
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. Work will emphasize the development and analysis of advanced methods in areas such as sparse signal recovery, compressed sensing, and statistical estimation, with a particular focus on their role in