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experience performing in vivo biodistribution imaging to apply to an exciting project investigating antibody penetration in heterogenous tumor models. The postdoc will work closely with in vivo imaging
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evaluate machine learning approaches for predicting clinically successful drug targets. For this work, the postdoc will have access to a large high-performance compute cluster and to AbbVie's cutting-edge
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guidance for computational modeling of the data Publish research in peer-reviewed journals and present work at scientific conferences aligned with business objectives Demonstrate a high degree of
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Max Planck Institute for Biological Intelligence (Seewiesen site), Seewiesen | Germany | about 3 hours ago
sleep while paddling from one place to another. Using custom data loggers developed by Ulanovsky’s lab, we will perform high-density neuronal recordings of single neurons in freely-swimming geese
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therapy program to expand professional network and research experience. The postdoc may be based at either our North Chicago, IL or Cambridge, MA sites, and will work closely in a collaborative and
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Generate new research strategies to effectively address the needs of the postdoc project Collaborate with functional and technical experts to facilitate scientific achievement Maintain a high level of
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that such institutions be the recipients of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical
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information about AbbVie, please visit us atwww.abbvie.com . Follow @abbvie onX ,Facebook ,Instagram ,YouTube ,LinkedIn andTik Tok . Job Description Program Overview AbbVie needs outstanding individuals willing
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potential, small angle X-ray scattering). Advanced computational and data analysis skills in biological systems. Familiarity with high-throughput experimental techniques and AI/ML applications in research
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experience with coding in R, Matlab and/or Python, and already adapt to using the UNIX command line and executing analyses using high performance computing cluster. Preferred qualifications: Prior experience