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this date. Job description Recent improvements in machine learning have dramatically improved the accessibility of de novo protein design. In this project, we seek to exploit these developments to interrogate
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. As a Carnegie Doctoral/R2 institution, our world-class scholars instruct about 26,000 students in associate's, bachelor's, master's and doctoral level degree programs. Whether you are seeking the charm
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and/or application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The tasks include primarily leading and conducting research
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for an excellent young life science or computational researcher to become Group Leader. Fellowships are targeted towards applicants to start their first independent group within a few years of their PhD. We offer
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for an excellent young life science or computational researcher to become Group Leader. Fellowships are targeted towards applicants to start their first independent group within a few years of their PhD. We offer
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. As a Carnegie Doctoral/R2 institution, our world-class scholars instruct about 26,000 students in associate's, bachelor's, master's and doctoral level degree programs. Whether you are seeking the charm
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. • Develop computational and theoretical models that bridge neural data and behaviour, leveraging modern machine‑learning toolkits. • Drive multi‑lab collaborations across SCENE; co‑author high‑impact
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single-cell transcriptomic data. The candidate should be proficient in, or highly motivated to learn cancer data science, machine learning, and high throughput sequencing analysis. Successful applicants
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resulting from T regulatory (Treg) cells by conducting genetic screens to overcome this suppression and to enhance CAR T cells for lymphoma. On the other hand, we also seek to apply the lessons learned from
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research, UTA is designated as a Carnegie R-1 “Very High Research Activity” institution. UTA ranks No. 4 nationally in Military Times’ annual “Best for Vets: Colleges” list and is among the top 30 performers