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research. This exciting position offers a unique opportunity to develop cutting-edge Knowledge Guided Machine Learning (KGML) methods for advancing our understanding of agroecosystem carbon and nitrogen
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in characterizing hit compounds identified through high-throughput screening (HTS) campaigns, as well as studying HIV-1 resistance-associated mutations (RAMs), utilizing a recently developed HIV-1
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of samples in line with the proposed aims/approach for the funded projects Preparation of manuscripts Development of new/follow-on hypotheses stemming from other studies Method development to address new
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researchers Analysis/documentation of analyses of samples in line with the proposed aims/approach for the funded projects Preparation of manuscripts Development of new/follow-on hypotheses stemming from other
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researchers Analysis/documentation of analyses of samples in line with the proposed aims/approach for the funded projects Preparation of manuscripts Development of new/follow-on hypotheses stemming from other