13 high-performance-computing-postdoc Fellowship positions at AbbVie in United States
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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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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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performance. The postdoc will apply their skills and expertise to develop tools to bridge this gap and solve our most cutting-edge drug delivery challenges. Responsibilities Generate new research strategies
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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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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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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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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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, or related approaches. Hands-on experience in high-throughput screening techniques for protein interactions and degradation pathways. Familiarity with computational tools for data analysis and bioinformatics
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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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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