IBED computational support team
For advice and support, contact us at compsup-ibed@uva.nl or see our personal pages to find a team member with specific expertise. In addition, check out our website which has more information and guidelines about computational resources and expertise available to IBED students and staff.
The team is available to IBED scientific staff and students to help:
- Access the best possible data sources and computational tools for your research including software, high-performance computing, web interfaces and advanced programming
- Develop analysis workflows
- Use innovative techniques to visualize data and results
- Provide written tutorials, hands-on training and documentation for specialized workflows and software
For questions or problems pertaining to ICT facilities (i.e. issues with wifi, wired network, workstation, laptop, hardware, etc.) please contact ICT Services.
The Computational Support team currently has six dedicated members and is part of the Lab & Infrastructure unit that supports the four IBED departments.
Our team has developed RDM guidelines for documentation of data and analysis code, including best practices on how to build a database model and how to link databases to analysis software. Documentation on best practices and helpful templates for RDM are available for all our staff.
IBED staff and students have several options available for safely storing active and inactive data in the short-term and long-term through services provided by SURF. We can help you decide which option is best for you, although direct support for these services is provided by the SURF help desk.
Our team provides can provide advice about advanced programming, development of complex data processing pipelines and use of high performance computing. If a project is too big in scale for personal computers, we can help with services provided by SURF and university ICT
One member of our team is dedicated to providing advice and supervision to scientists, postdocs, and PhDs around bioinformatic data analyses. She also develops new workflows and has experience in metagenomics, phylogenomics and amplicon data analysis.
Our team’s machine learning engineer and computer vision engineer is experienced in developing automated and robust methodologies. Our engineer closely collaborates with students and scientific staff on research and is also highly skilled in the use of high performance computing infrastructures.
The team is skilled in the processing, management and knowledge transfer of geodata and is available to help with spatial data analysis using Geographical Information Systems and remote sensing (RS) software. We are also involved in research and education done at the institute’s GIS-Studio.
We actively collaborate with SURF, the Faculty of Science specialist ICT support group (FEIOG) and the Swammerdam Institute for Life Sciences (SILS) to coordinate high-performance computing and dedicated, secure storage for unusually large datasets. We are linked to the institute’s GIS-Studio which assists students and staff with spatial data analysis and provides them with up-to-date fieldwork equipment. We also contribute to tools and facilities developed by IBED departments.
We are also available to help you discover and use existing UvA resources related to:
- Research data management
- Drawing up a data management plan
- University policy regarding data management
- Securely storing active data and archiving data
- Sharing published data
- Training and workshops like those offered by the Amsterdam Science Park Study Group and SURFsara