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Fusion Tribrid MS and Waters Q-ToF instruments are highly desired. Experience handling and analyzing large-scale MS, MS(MS) and/or proteomics-like datasets using statistical and machine learning techniques
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healthcare data. * A team player who thrives as a member of a highly functional cross-disciplinary team Preferred Elements * B.S, M.S., and/or PhD in Computer Science, Biomedical Informatics, Machine Learning
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of alumnus Dev Joneja, PhD ‘89. Maxwell Fellows provide a bridge to enhance collaboration among faculty developing cutting edge tools in data science and in biomedical research, potentially spanning
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is expected that the postdoc in this position will seek funding (e.g., an NIH NRSA award) for continuing the position after the first year. Applicants must have completed the PhD by the date
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: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Design nucleic-acid nanostructures and assemble them in a wet laboratory
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about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Develop DNA-based sensors that seed crisscross assembly of single
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adverse events to inform standard ER analyses for safety and provide complementary tolerability data to improve dosage optimization strategies in oncology clinical trials. Learning Objectives: As an ORISE
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Medical - Clinical Medical - Research Internal Number: A-179907-11 General Description The laboratory of Gislin Dagnelie, PhD, Lions Vision Research and Rehabilitation Center, Johns Hopkins Wilmer Eye
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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods
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with real-world samples, and effectively integrating them with microfluidics as a standalone device. This is a great opportunity to learn new skills, contribute to assay development, and intellectually