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expertise in machine learning and/or Bayesian models is preferred. This position will involve both methodology development and analysis of multi-omic sequencing data, including spatial transcriptomic data
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technically proficient in basic wet lab techniques, including primary and cell line culture, viability assessment, cell cycle analysis, cytotoxicity, proliferation, migration analysis, PCR, Western blotting
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sequencing analysis and computational approaches while contributing to collaborative academic and industry projects. Mentorship will be provided by Dr. Petljak, who will offer guidance in translating research
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analysis Ability to work in a collaborative and team environment Excellent oral and written capabilities Expertise in two or more of the following areas: Experience in sample preparation for mass
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of those T lymphocytes recognizing tumor cells shall be performed using scRNAseq and paired TCR sequencing. FACS analysis by multiparameter flow, functional real time CTL assays, retroviral/lentiviral
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strong background in computer science and bioinformatics analysis of large datasets. The applicant should be highly self-motivated and have a track record of publications (first-authored publications in
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functional profiling data. The successful candidate will be involved in all aspects of the research from initial processing of the biopsy specimen to organoid culture and drug sensitivity analysis. Located in