35 condition-monitoring-machine-learning Postdoctoral positions at University of Maryland, Baltimore
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; Embraces and actively promotes an inclusive and equitable work environment. Experience conducting mixed-methods research, including quantitative and qualitative analytical skills; Proficient computer skills
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science on bacterial pathogens with translational implications for worldwide impact. This position would provide opportunities to learn novel cell modeling systems and immune response characterization and
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, affirmative action employer . All qualified applicants will receive consideration for employment regardless of sex, gender identity, race, color, religion, national origin, disability, protected veteran status
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research background in molecular and cellular biology. Research in our lab focuses on epigenetic and genetic mechanisms of pathologic conditions that occurred during liver and kidney transplantation by using
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molecular and cellular evaluations of conditions affecting long-term graft outcomes in solid organ transplant recipients. Overall, we apply systems biology approaches toward implementation of precision
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for employment regardless of sex, gender identity, race, color, religion, national original, disability, protected veteran status, age, or any other characteristic protected by law or policy . We value diversity
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to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy. We value diversity
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on epigenetic and genetic mechanisms of pathologic conditions that occur during liver and kidney transplantation by using state-of-the-art technologies such as single cell genomics. This opportunity provides
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experimental procedures and results in a detailed laboratory notebook and computer databases. Analyze data using statistical software. Prepare graphics to present data at conferences and in manuscripts
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qualified applicants will receive consideration for employment regardless of sex, gender identity, race, color, religion, national original, disability, protected veteran status, age, or any other