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- 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.13
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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.12
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- This course is included as part of several DTP and MPhil programmes11
- Those with programming experience in other languages that want to know what R can offer them11
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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
- data managers6
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- 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.5
- Life sciences5
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- The course is open to Graduate students5
- This course is aimed at students and researchers of any background.5
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- We assume no prior knowledge of what a HPC is or how to use it.5
- postdocs5
- software developers, bioinformaticians5
- Anyone intersted in GWAS and using the H3Africa genotyping chip4
- Bioinformaticians and wet-lab biologists who can program in Perl, Python or R. 4
- Biomedical researchers4
- Molecular Biologists4
- Novice users of HPC and anyone who expects to need to use HPC systems at some stage in their research4
- Pathologists4
- Research presentation4
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- This course is aimed at researchers with an interest in metabolomics and its applications4
- This workshop is aimed at researchers interested in proteins4
- This workshop is aimed at researchers who need to undertake sequence searching as part of their work4
- Wet-lab Researchers4
- beginner bioinformaticians4
- database managers4
- network analysis4
- or who need to search against several biological datasets to gain knowledge of a gene/gene set4
- protein-protein interactions and related areas4
- health professionals3
- <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">.3
- Anyone who wants to become a teacher / trainer or a better one3
- Beginner3
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- Bioinformaticians and wet-lab biologists who can program in Python or R. 3
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- The course is aimed at <b>bench biologists and bioinformaticians</b> who need to analyse their own data against large biological datasets3
- The module is suitable for researchers interested in gene expression analysis and visualisation3
- The workshop is aimed to biologists or computer scientists with little or no previous knowledge of Cytoscape3
- This course is aimed at advanced PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing technologies in cancer research and wish to familiarise themselves with bioinformatics tools and data analysis methodologies specific to cancer data. Familiarity with the technology and biological use cases of high throughput sequencing is required, as is some experience with R/Bioconductor (basic understanding of the R syntax and ability to manipulate R objects) and the Unix/Linux operating system. 3
- This introductory course is aimed at biologists with little or no experience in machine learning.3
- This workshop is aimed at researchers who are either generating or integrating molecular interaction data in their research. This could be protein-protein interaction as well as protein-RNA3
- This workshop is aimed at students on the Rare Diseases and Experimental Medicine MPhil courses at the University of Cambridge. Students from the wider clinical sciences group are also able to attend subject to space being available.3
- This workshop is aimed at wet-lab scientists and bioinformaticians. Participants should have degree-level understanding of molecular biology/genetics and be proficient at using web browsers. 3
- Training Designers3
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- bioinformatics and other life scientists planning to work with next-generation sequencing data.3
- data manager3
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