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- This course is funded as part of the UKRI Innovation Scholars. Data Science Training in Health and Bioscience call (DaSH). (MR/V038966/1)5
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Target audience
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- Everyone is welcome to attend the courses55
- please review the policies.54
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- as well as other departmental training within the University of Cambridge (potentially under a different name) so participants who have attended statistics training elsewhere should check before applying.28
- This course is included as part of several DTP and MPhil programmes23
- <span style="color:#FF0000">After you have booked a place22
- if you are unable to attend any of the live sessions and would like to work in your own time22
- including for registered university students.<span style="color:#FF0000">22
- please email the Team as Attendance will be taken on all courses. A charge is applied for non-attendance22
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- Master students20
- life scientists17
- PhD Students16
- This is aimed at life scientists with little or no experience in machine learning and that are looking at implementing these approaches in their research.16
- post-docs16
- All postgraduates15
- It may be particularly useful for those who have attended other Facility Courses and now need to process their data on a Linux server. It will also benefit those who find themselves using their personal computers to run computationally demanding analysis/simulations and would like to learn how to adapt these to run on a HPC.15
- This course is aimed at students and researchers of any background.15
- We assume no prior knowledge of what a HPC is or how to use it.15
- mixed audience15
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- The course is aimed at biologists interested in microbiology7
- This workshop is aimed at researchers interested in proteins7
- network analysis7
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- The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics6
- but who have not perhaps put this into practice since.6
- protein-protein interactions and related areas6
- researchers6
- Biologists and bioinformaticians5
- Engineers5
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- Masters students5
- Note that we will not cover specific topics in phylogenomics (whole-genome phylogenies) or bacterial genomics.5
- Postdoctoral researchers5
- The course is open to Graduate students5
- This course is - in abbreviated form - included as part of several DTP and MPhil programmes5
- This course is aimed at researchers with no prior experience in phylogenetic analysis who would like an introduction to the foundations of building phylogenies from relatively small sequences (viral genomes and/or targeted regions of eukaryotic genomes).5
- Trainers5
- but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.5
- software developers, bioinformaticians5
- Anyone intersted in GWAS and using the H3Africa genotyping chip4
- Anyone who is using sequencing as part of their work and/or research.4
- Bioinformaticians and wet-lab biologists who can program in Perl, Python or R.4
- Biomedical researchers4
- DMP writers4
- Data Managers4
- Early Career Researcher4
- Early Career Researchers (ECRs)4
- Familiarity with mass spectrometry or proteomics in general is desirable4
- Life Scientists4
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- Novice users of HPC and anyone who expects to need to use HPC systems at some stage in their research4
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- Researchers who want to extract quantitative information from microscopy images4
- The course is targeted to either proteomics practitioners or data analysts/bioinformaticians that would like to learn how to use R to analyse proteomics data.4
- This course is aimed at researchers with an interest in metabolomics and its applications4
- This workshop is aimed at researchers who need to undertake sequence searching as part of their work4
- Training Designers4
- Training instructors4
- Wet-lab Researchers4
- beginner bioinformaticians4
- bioinformatics and other life scientists planning to work with next-generation sequencing data.4
- database managers4
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- Impact of research infrastructures5
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