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Dupin. We have recognized expertise in pulmonary physiology and pathophysiology and develop 3D in vitro models based on innovative cell culture and imaging techniques. Where to apply E-mail job-ref
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neurodegenerative diseases, with a specific focus on immune cell exhaustion and immunosenescence in the peripheral immune system. Our long-term research mission is to leverage such mechanisms to develop more
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
collaborators, the researcher will design and execute experiments that move technologies from discovery toward real-world clinical applications. Key responsibilities include developing and optimizing biomaterial
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Researcher (R1) Application Deadline 10 May 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework
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or Departmental Website: https://med.stanford.edu/gruberlab.html (link is external) How to Submit Application Materials: Interested applicants should submit the required application materials by email to Aronne
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. * Knowledge of general principles in cell/molecular biology. * Experience in standard cell/molecular biology techniques, such as Western blotting and PCR. Essential Duties: * Research Development and Execution
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an evaluation of titles and examination, by means of an interview. Additional comments Annual budget: 22500 Frequency of calls: no International mobility required: no Website for additional job details https
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, specifically supporting single-cell sequencing and long-read sequencing library preparation. Perform biochemical, cell culture, and animal experiments to elucidate molecular mechanisms underlying mutagenesis
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multidisciplinary team of experts in molecular/cell biology and chemistry, you will play a pivotal role in bridging the gap between biological discovery and clinical application. You will be responsible for isolating
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. The successful candidate will apply and develop bioinformatics, statistical, machine learning, and deep learning approaches to analyze single-cell sequencing and spatial expression data, including single-cell RNA