ASK AN EXPERT

meet with an expert who wants to help you

Do you need help planning your research project?

Are you having trouble analyzing your data or deciding which computational tool to use so you can move forward with your research?

The Amsterdam Science Park Study Group has a team of experts willing to meet with you and help solve your problems.

This support activity is free of charge but primarily targeted at SILS and IBED members.

Here is a list of our experts. Email one of us to set up a free meeting, in person or online:

• Statistics, experimental design: Huub Hoefsloot (Associate Professor, SILS), Emiel van Loon (Associate Professor, IBED).
• Bioinformatics, genomics, Snakemake, R: Tijs Bliek (Technician, SILS),
• Bioinformatics, machine learning, processing large datasets: Frans van der Kloet (Research Assistant, SILS),
• Genomics, data management, data science with R and Python, machine learning: Marc Galland (Data scientist),
• R & Shiny, data visualization, image analysis: Joachim Goedhart (Assistant Professor, SILS),
• R, Shiny, SQL, Databases, online tools for visualizing data: Johannes de Groeve (Data Manager),
• R, geospatial data analysis, GIS, data management, data repositories: Stacy Shinneman (Geoinformatician, IBED),
• Image analysis, machine learning, high performance computing: Casper Thuis (Data Engineer, IBED).

Not sure who to contact? Problem not listed here? Please, contact Tijs Bliek.

See our People page for more details about each group member’s expertise.

Please include the following information in your email

• a short description of your research question
• the main goal for your experiment or project: what do you want to learn?
• details about prior data or prior knowledge (e.g. has someone in your lab or team already done the same or a similar experiment)?
• do you know how to analyse your data and results?

Ask questions. Get answers. Solve problems. Make connections.

• How many samples should I collect to get proper statistical results?
• How do I plan for statistical analysis before starting my experiments?
• What are the best computational tools and resources for my project?
• What software or pipelines should I use? Where can I find training in specific techniques?
• Do I need to develop my own software? How would I start doing that?
• How can I learn more about computational techniques like modeling, image analysis and machine learning?