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. Candidates with background knowledge and hands-on experience in mouse models, proteomics, 3D organoids, primary cell purification, and culture skills are particularly welcome. Requirements: A PhD or MD/PhD
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) and arthritis pain (e.g. psoriatic arthritis pain), with a focus on ion channels and neural circuits. Candidate must have completed the requirements for the PhD degree or equivalent in Neuroscience
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directly with the PI on applying interdisciplinary neuroscience and electrophysiology techniques toward studying the nervous system of the heart. Qualifications: Education 5 years or less from a PhD or MD
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; the candidate may present evidence of completion of the degree requirements, together with a statement documenting the date on which the degree is to be conferred. The candidate will have a minimum of a PhD
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. The Schumacher laboratory in the Department of Biochemistry at the Duke University School of Medicine seeks a Postdoctoral fellow with expertise in Cryo-EM data collection, data processing, generation of cryo-EM
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will perform the following tasks: • Design, implement, and maintain scalable computational pipelines for multi-omics data, including bulk/single-cell RNA-seq, spatial transcriptomics, metagenomics
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position is funded by multiple NIH projects, e.g., https://tinyurl.co m/ysxhmujvThe overall goal is to : (1) develop inference and dynamic prediction models using a wide variety of data, including clinical
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opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status
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to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual
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of immunology and molecular biology preferred. Candidates should have excellent scientific writing and strong oral communications skills Experience in leading research papers for publication and data