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Field
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; survival or hazard models; gradient-boosted decision trees or related predictive approaches; interpretable feature-importance methods; Git/GitHub; Linux or command-line workflows; preregistered analyses; and
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; Assess the effect of using organo-mineral resources on soil carbon stock in the field; Implement agronomic assay to evaluate the stability of clay-humic complexes under culture conditions and how
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, analyze, and interpret experimental data to assess process performance, stability, and scale-up considerations Support development of process documentation, including test plans, operating procedures, and
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Responsibilities Develop and formulate new simple and complex fertilizer products Contribute to the optimization of fertilizer formulations to improve nutrient stability, homogeneity, physical quality, and agronomic
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expertise on epigenetic and epitranscriptomic modifications, DNA repair and genome (in)stability, single-cell and single-nucleotide analysis, embryology and healthy development. Read more about CRESCO here
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built on that genomic work. Responsibilities: Design and execute field and controlled-environment pathology experiments, including inoculum-density gradient studies; direct undergraduate research interns
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for: Conducting leading‑edge theoretical research in feedback control and mathematical systems theory Developing new robustness and feedback stability analysis results for nonlinear feedback systems subjected
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, selectivity, stability, and scalability of electro-enzyme coupled catalysis systems. You are expected to conduct independent and collaborative research, publish in peer-reviewed journals, present results
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Conduct research in high harmonic generation, ultrafast XUV science and related applications. Develop and optimize HHG sources, diagnostics and experimental methods, with emphasis on photon flux, stability
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docking to investigate viral spike/capsid architecture, thermal stability, and immune epitope accessibility. AI/Deep Learning: ML/DL model development (e.g., PyTorch, Lightning) for predicting antigenicity