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models (rodent handling/surgery experience a plus). ● Familiarity with quantitative/computational approaches (e.g., R, Python, image analysis, statistics) is a plus but not required. ● Ability
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. Major responsibilites: The candidate will work independently to purify recombinant IDR constructs and label them for F19-NMR analysis. In parallel, the candidate will use Python for bioinformatics
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epigenetics of acute myeloid leukemia and has published articles in Cancer Cell, Cell, Leukemia, and the New England Journal of Medicine. The lab has extensive expertise in both bench science and bioinformatics
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research project in any of several areas relevant to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic
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to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic screens, biochemistry, ribosome profiling (ribo-seq
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applications with related expertise. Experience with sequencing approaches to study RNA turnover or with massively parallel reporter assays(MPRAs) will be beneficial. Must Have Bioinformatics experience in
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computing and quantum advantage is a prospective topic across four application domains: bioinformatics, breeding, biomaterial synthesis, and cellulose‑processing enzyme design. You will develop hybrid quantum
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: bioinformatics, breeding, biomaterial synthesis, and cellulose‑processing enzyme design. You will develop hybrid quantum‑classical algorithms to tackle domain‑specific, computationally demanding problems. Methods
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methods are developed in parallel, the postdoc will develop systems and services that make biological data accessible to AI and computational tools, collaborating closely with the Human Protein Atlas (HPA
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association study (GWAS) summary statistics. Analyze single-cell and bulk genomics datasets using standard and custom bioinformatics pipelines. Contribute to grant writing, manuscript preparation, and