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Field
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the lab to real-life applications, improving lives. We are seeking a highly motivated postdoctoral researcher (f/m/x) to develop advanced physical and computational models integrating transcriptional and
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. - Conduct high-throughput serum proteomic analyses and integrate molecular datasets. - Validate candidate biomarkers in independent cohorts. WP3.2 – Integrated predictive modeling: - Develop integrative multi
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. The candidate will engage in cutting-edge research employing molecular and chemical biology techniques, including LC-MS metabolomics, flow cytometry, mouse model studies, genomics, proteomics and bioinformatics
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molecular imaging research program. This platform will support translational studies mainly in oncology, through quantitative multimodal imaging (PET-CT, SPECT-CT, optical imaging, autoradiography
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of nutrition and health, with the aim of understanding the molecular basis of nutrition-dependent diseases, and of developing new strategies for treatment and prevention (https://www.dife.de/en/). We invite
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 29 days ago
biophysics/chemistry. Programming skills (e.g., bash scripting, python, Fortran, C++ and CUDA), expertise in computational modeling (such as Molecular Dynamics, virtual screening, free energy calculations and
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, molecular biology, biochemistry, immunology, or related field, with a strong focus on murine myopathy models. Demonstrated experience in in vivo experimentation, including animal handling, dosing, tissue
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solutions for integrating multiple biological modalities and to establish a link between the phenotype observed under the microscope and various molecular measurements of the cell. The methods will be
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combines advanced 3D stem cell modeling, neuroimmune interaction studies, high-content imaging, molecular and biochemical analyses and the evaluation of immunomodulatory therapeutic strategies in MSA. Key
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: Computational, Quantitative, and Predictive Modeling of Root Systems. This position emphasizes integration of phenomics and other -omics data into predictive frameworks. Research areas may include: Structural