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Position Summary A postdoctoral position is available in the laboratory of Dr. Andreas Kautt in the Department of Biology on the Danforth Campus at WashU in St. Louis. The Kautt Lab studies
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) biomaterials, soft lithography, and hydrogel synthesis, and (c) cell culture and molecular cell biology assays. The successful candidate is expected to publish papers in prestigious peer-reviewed journals and
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Biology, Deep Learning, Histology, Immunochemistry, In Vivo Imaging, Micro-Computed Tomography (Micro-CT), Mouse Handling Questions For frequently asked questions about the application process, please refer
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About This Job Preferred Qualifications: Ph.D. in Electrical Engineering, Physics, Applied Physics, Biomedical Engineering, Computer Engineering, or related fields. Experience with Silicon photonics
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are looking for a postdoctoral researcher with physics or engineering expertise who will design and operate a 3D super-resolution ultrasound system, write control software, build computational imaging pipelines
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in the Required Qualifications section. Skills: AI Concepts, Biology, Technology Development Questions For frequently asked questions about the application process, please refer to our External
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Position Summary Candidate will conduct full-time research on topics including novel histone modifications (epigenetic marks) and their role in immune regulation, cancer and metabolism. Job Description Primary Duties & Responsibilities: Information on being a postdoc at Washington University in...
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on technical questions, manuscript writing and data analyses. Provide support for the skill building activities of the QuEST Network though knowledge sharing activities, preparing online courses and in-person
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repository and computer servers. Run existing PET/MR brain image processing pipelines on the computer servers, produce the results, and communicate with the group members. Write computer codes for the above
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based on new discoveries from next generation sequencing. The successful candidate will participate and lead research projects using computational biology approaches to address questions that are both