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Sponsor
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Target audience
- Institutions and other external Institutions or individuals569
- Postdocs and Staff members from the University of Cambridge569
- Graduate students568
- Everyone is welcome to attend the courses98
- please review the policies.97
- 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.39
- This course is included as part of several DTP and MPhil programmes30
- <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
- This course is aimed at students and researchers of any background.21
- We assume no prior knowledge of what a HPC is or how to use it.21
- 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.16
- 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
- This course is open to everyone who is interested. Have a look at our guidelines.12
- Bioinformaticians and wet-lab biologists who can program11
- Existing R users who are not familiar with dplyr and ggplot211
- The course is aimed at biologists interested in microbiology11
- Those with programming experience in other languages that want to know what R can offer them11
- This course is - in abbreviated form - included as part of several DTP and MPhil programmes9
- 2025/26 Wellcome Sanger Institute student cohort and staff members7
- Anyone who is using sequencing as part of their work and/or research.7
- Note that we will not cover specific topics in phylogenomics (whole-genome phylogenies) or bacterial genomics.7
- Researchers who are applying or planning to apply image analysis in their research7
- 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).7
- This workshop is aimed at researchers interested in proteins7
- but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.7
- network analysis7
- Familiarity with mass spectrometry or proteomics in general is desirable6
- The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics6
- 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.6
- but who have not perhaps put this into practice since.6
- prokaryotic genomics and antimicrobial resistance.6
- protein-protein interactions and related areas6
- Attendees of our training courses on specific applications (e.g. RNA-seq5
- Biologists and bioinformaticians5
- ChIP-seq5
- HPC users who would like to learn how to manage software and automate and parallelise analyses using available pipelines.5
- It may be particularly useful for those who have attended other 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
- No prior experience in the analysis of these types of data is required.5
- Researchers who are starting to run bioinformatics analysis on their own.5
- The course is open to Graduate students5
- This course is aimed at researchers with an interest in metabolomics and its applications.5
- analysis of complex microbiomes and antimicrobial resistance.5
- etc.) will greatly benefit from this course.5
- prokaryotic genomics5
- variant calling5
- Biologists4
- Novice users of HPC and anyone who expects to need to use HPC systems at some stage in their research4
- Researchers who want to extract quantitative information from microscopy images4
- 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
- bioinformatics and other life scientists planning to work with next-generation sequencing data.4
- or who need to search against several biological datasets to gain knowledge of a gene/gene set4
- wet-lab scientists4
- <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">.3
- Institutions and other external Institutions or individuals.3
- Institutions and other external institutions or individuals.3
- Postdocs and other Research Staff from the University of Cambridge3
- Postdoctoral Researchers3
- Students who have some basic familiarity with Python. There are no prerequisites for knowledge of biology or statistics. The course is designed for those who want to learn how to apply unsupervised machine learning techniques to real-world datasets. Please review the policies3
- The course is aimed at <b>bench biologists and bioinformaticians</b> who need to analyse their own data against large biological datasets3
- The course is aimed at people at postgraduate level who are involved in research.3
- The course is open to Postdocs and Staff members from the University of Cambridge3
- 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 targeted at life scientists who would like to explore how AI chatbots can be used to support their data analysis3
- This introductory course is aimed at biologists with little or no experience in machine learning.3
- 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
- Wet-lab Researchers3
- pathways and diseases.3
- programming and bioinformatics tasks.3
- 2025-26 SBS MPhil cohort2
- <span style="color:#0000FF"> Non-members of the University of Cambridge to pay £575 </span style>2
- <span style="color:#0000FF">All Members of the University of Cambridge to pay £250 </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>2
- <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">2
- All CCRIT (formerly BTF) trainers2
- Anyone wanting to use OMERO to organize2
- Applicants are expected to have a working knowledge of R.2
- Biological sciences research students and postdocs who may want to use HPC in their research. Please note that Biochemistry first year graduate students book this course via their Moodle site not here.2
- Cytoscape will have to be downloaded and installed on your device for the practical sessions.2
- Facility Managers wanting to train users2
- Further details regarding eligibility criteria are available here2
- Guidance on visiting Cambridge and finding accommodation is available here. <div class="heading">Bookings and fees</div> Please note that all participants attending this course will be charged a <b>registration fee</b>. The fees are as follows:2
- Institutions and other external Institutions2
- Part of CRUK Bioinformatics Summer School:Unix and R Foundations 20222
- Participants organised through CRUK Cambridge Centre2
- PhD Students2
- PhD students2
- Please review the policies.2
- Principal Investigators2
- Principal Investigators from the University of Cambridge2
- Students and researchers from life-sciences or biomedical backgrounds2
- Suitable for students and early career researchers2
- The course is recommended for all staff and students who use Linux in their research or plan on attending the CI High Performance Computing facilities (Cluster) course.2
- This course is aimed at researchers dealing with or planning to perform chemical analysis.2
- This course is aimed at researchers with no prior experience in the analysis of ChIP-seq data2
- This course is for researchers from a broad biological background as the techniques learned can be applied to any InterMine database2
- This is a follow-up session dedicated specifically for students & staff who have attended Models and/or Models2
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