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candidate needs to have expertise in molecular virology and live calcium imaging with specific experience in rotavirus, caliciviruses, enteroviruses, adeno-associated virus transduction, and computational
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AI-modeling and coding. The successful candidate will work alongside a multidisciplinary team, leveraging artificial intelligence and computational methodologies to optimize treatment plans, enhance
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research program integrates state-of-the-art genomic and molecular approaches—including ribosome profiling, CLIP-seq, single-cell multiomics, CUT&Tag, and long-read sequencing—to elucidate gene regulatory
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MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications PhD in computational science Working knowledge of machine learning and deep learning 3
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computer science. These skills would be applied to large mass spectrometry and mass spectrometry imaging datasets for clinical research, focusing on malignancies including breast and lung cancer and intraoperative
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using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Successful
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intended for life science graduates from Immunology or Microbiology backgrounds, however, a graduate with background in Computer Science or Computational Biology will also be considered. The successful
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. Experience with computational analysis of NGS sequencing data and/or experience with mouse models is a plus. Job Duties Under the general direction of the PI: Design, plan, and conduct research experiments
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bioinformatics, statistics, and/or computer science to join the Eberlin Lab for Medical Mass Spectrometry. These skills would be applied to large mass spectrometry and mass spectrometry imaging datasets
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biologically/pharmaceutically important proteins for cancer therapy. In addition, the candidate will receive training in computational drug design, biochemistry and cell biology techniques for testing compound