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strategies, we aim to contribute to the development of next-generation prodrugs while expanding the synthetic toolbox. As such, this PhD project combines method development with catalysis and organic synthesis
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ingredients, a process that is traditionally slow because each substrate–strain combination behaves differently. By applying machine learning to historical experimental data, we can predict high‑potential
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; applying and combining advanced analytical techniques, such as chromatography, mass spectrometry, and NMR, for the characterization and functionalization of biopolymers for biobased materials. Affinity with
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