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- HDRUK14
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Scientific topic
- Bioinformatics1099
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- Workshops and courses21
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- United Kingdom15
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Target audience
- Institutions and other external Institutions or individuals14
- Postdocs and Staff members from the University of Cambridge14
- Graduate students13
- Researchers who are applying or planning to apply image analysis in their research4
- Researchers who want to extract quantitative information from microscopy images4
- Anyone wanting to use OMERO to organize2
- Facility Managers wanting to train users2
- annotate and publish imaging data2
- view2
- <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Members of Industry to pay 575.00 GBP. </span style> <span style="color:#0000FF">All Members of the University of Cambridge1
- Affiliated Institutions and other academic participants from External Institutions and Charitable Organizations to pay 250.00 GBP. </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>1
- Anybody interested in using Jupyter and OMERO1
- BioImage Analysts with some experience of basic microscopy image analysis1
- Biophysicists1
- Cell Biologists1
- Day1 is intended for biologists and computer scientists interested in using LithoGraphX. Some experience in imaging is desirable but not required.1
- Day2 is intended for computer scientists wanting either to write their own algorithm or automate complex protocols. Basic python knowledge and familiar with C++ are required.1
- Facility Managers using or1
- Life scientists with programming skills1
- OMERO for image data management1
- The course is open to Graduate students1
- This course is aimed at scientists working with biomage data across the life sciences. It is suitable for those involved in creating bioimages or taking their first steps in analysis. The content would also be suitable for those wanting to learn more about the BioImage Archive and gain experience with machine learning approaches for image analysis. The programme will be of particular interest to bioimage analysts with questions relating to the use of ‘big data’ and using the wealth of publically available data curated in the BioImage Archive. The course should be accessible to members of the bioimaging community and does not require prior experience with machine learning methods or use of the BioImage Archive. Applicants are encouraged to explore the resources below before starting their application. Applicants should be comfortable with basic programming tasks and have experience working with Python. Prerequisite reading: BioImage Archive: A call for public archives for biological image data ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy The BioStudies database - one stop shop for all data supporting a life sciences study EMPIAR: a public archive for raw electron microscopy image data Image Data Resource: a bioimage data integration and publication platform BioImage Model Zoo 1
- This course is appropriate for researchers who are relatively proficient with computers but maybe not had the time or resources available to become programmers.1
- This course may be of interest to physical scientists looking to develop their knowledge of Python coding in the context of bioimage analysis1
- bioinformaticians and image analysts.1
- wanting to use1
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- First come first served1
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