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population genomic analyses of crop species Experience managing and analyzing large-scale biological datasets Experience using SLURM-based high-performance computing systems Demonstrated proficiency in R
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data in a high-performance computing environment. Assist in the mentorship and supervision of more junior lab members. Interpret experimental results and prepare reports, presentations, and scientific
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applied magnetic field. A major part of the project will also include close collaboration with theoretical and computational materials scientists. The postdoc will perform targeted exploratory reactions in
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Preferred Qualifications: Experience performing molecular biology techniques, including DNA isolation, RNA isolation, PCR, qPCR, and gene expression analysis. Experience operating high-performance liquid
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to federal research proposals, sponsored research applications, and collaborative project reports. Familiarity with scalable computing environments, cloud platforms, high-performance computing, distributed AI
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, transcriptomic, and proteomic datasets to uncover biological mechanisms and generate novel research insights. The successful candidate will apply bioinformatics and statistical approaches to analyze high
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containers or crucibles, and performing high-temperature reactions using induction heating, tube furnaces, box furnaces, vacuum/inert atmosphere processing, or related thermal processing methods
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applications in biological and quantum materials. The work will include developing, planning and performing experiments, critically analyzing results, performing optimization to improve outcomes, and generating
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research assistants to ensure high-quality data and sample integrity. The Postdoc will perform bioinformatic and statistical analyses of microbiome, soil, and plant datasets using tools such as R or Python