Call for participation

Call for participation

Alicia Janz

Alicia Janz

I have a background in linguistics with a specialization in phonetics. Prior to joining the DKZ.2R I studied verbal and multimodal feedback in conversation with a focus on intonation and conversational context. In December of 2023 I started working for Forschungszentrum Jülich where I am currently the main project coordinator for the DKZ.2R. To contact me or my colleague Katharina Immel you can send an e-mail to: info[at]dkz2r.de.

Call for participation!

The Data Literacy Center Rhine-Ruhr (DKZ.2R) issues a call for participation in its “rent-an-expert” project! We offer support for ambitious research projects of PhD students and early postdocs dealing with Data Science and Artificial Intelligence, High Performance Computing and Simulation, and Research Data Management. As the DKZ.2R is funded by the German Federal Ministry of Education and Research (BMBF) as well as the EU, this offer is free of charge!

What is the DKZ.2R?

The DKZ.2R aims to reduce data-related hurdles in research by supporting scientists in improving their methodological data-related skills. We are a consortium of nine institutions in the Rhine-Ruhr area, including universities, research institutions, and universities for applied science. One of the main goals of the DKZ.2R is to identify and connect different projects and efforts to support scientists in their work with research data. To this end, we connect researchers directly, foster their collaboration, and aid using resources as efficiently as possible.We currently establish different support structures including research consulting via research tandem projects and informal gatherings like Data Cafés and hackathons. Our “rent-an-expert” project offers short- or long-term support by expert consultants from the fields of e.g. Machine Learning, Research Data Management, and High Performance Computing.

What we are looking for:

We invite applications from all early-career researchers (PhD students, early postdocs, masters’ students in special cases) who are planning or already working on a project in which they are facing data-related hurdles. We are especially, but not exclusively, looking for projects in life sciences, natural and engineering sciences, mathematics, and supercomputing. Anyone to whom scientific consulting could be beneficial is encouraged to apply!

What we are offering:

Each chosen applicant is offered an introductory meeting (around two hours) in which the applicant and consultant get to know each other. Here, the applicant also introduces the (planned) project and describes the data-related problem and expected or encountered difficulties. Furthermore, this meeting will be used for the applicant and consultant to align their project-related expectations and to determine whether long-term support is viable. There could be different short-term and longer-term consulting scenarios. Some example scenarios are illustrated in the following:

Scenario 1, short-term consulting: With an existing implementation for processing data, performance metrics deteriorate or fundamental runtime problems occur when the data volumes under consideration are expanded. The DKZ.2R consultants can help to identify and localize the causes and provide initial indications of a solution (e.g., by suggesting alternative Deep Learning architectures or GPU-parallelization approaches) .

Scenario 2, longer-term consulting: The processing of large amounts of data requires concepts and algorithms that enable an implementation and efficient execution in a high-performance environment. DKZ.2R consultants provide support in the concept development phase and assist applicants in the implementation phase.

Ultimately it is up to you and your consultant to decide for how long and in what frequency you would like to be supported in your project.

Application requirements:

All applications must be submitted in PDF format via e-mail (subject: “Application Scientific Consulting’’) to info@dkz2r.de by August 5, 2024, 5 p.m. (UTC+2). Applications must be written in Times New Roman, 12pt. (or equivalent) with a line spacing of 1.5. The applications should be 1–1.5 pages long and must include the following information:

  • A short description of the (planned) scientific project and its planned duration. How is data literacy particularly relevant in this project? Does the applicant receive any financial funding or non-material support for the project?
  • Up to six keywords describing the (planned) scientific project.
  • The applicant’s background such as education, current position, and scientific domain, as well as a short summary of the applicant’s data-related skills in relation to the project.
  • The applicant’s ideas on how they potentially wish to be supported by a scientific consultant. Do you anticipate long- or short-term consulting? Does the project consist of different phases that might influence the frequency of the consulting? How specifically can a consultant support the project?

By submitting an application you agree that published material based on the cooperation with DKZ.2R will contain an acknowledgement and that a short report about your project will be submitted when the cooperation/project has concluded. Feel free to share this call with anyone who might be interested! For questions please check our website www.dkz2r.de or send us an e-mail at info@dkz2r.de.

Related Posts

Comments on Collaboration - My Experience with the DKZ.2R Rent-an-Expert Program

Comments on Collaboration - My Experience with the DKZ.2R Rent-an-Expert Program

Comments on Collaboration - My Experience with the DKZ.2R Rent-an-Expert Program

At the beginning of this year (2025), I received an email regarding the DKZ.2R “Rent an expert” program. I was very interested in this initiative and therefore applied for support from the scientific consulting team at the Rhine-Ruhr Center for Scientific Data Literacy (DKZ.2R) for assistance with my data analysis.

I obtained my master’s degree in Plant Nutrition from the China Agricultural University and pursued my PhD study at the University of Hohenheim. I am currently a postdoctoral researcher in the Institute of Crop Science and Resource Conservation, Crop Functional Genomics, at the University of Bonn.
My research expertise includes plant culturing, molecule cloning, biochemical analysis and limited data analysis experience on large-scale NGS datasets.
Since the beginning of April 2025, two DKZ.2R consultants were assigned to me: Tarek Iraki, who is proficient in programming languages such as Python, and Lennard Maßmann, who specializes in working with R. Together, we collaboratively worked on my Postdoctoral project, which focuses on the molecular and genomic dissection of lateral root development in maize.

Read More
Carpentries Workshop - Introduction to Python

Carpentries Workshop - Introduction to Python

Empowering Researchers with Foundational Computing Skills: Join the Upcoming Carpentries Workshop

In today’s fast-paced research environment, the ability to harness computational tools effectively can make a world of difference. Whether you’re managing data or automating tasks, having the right skills can significantly streamline your work. That’s where The Carpentries come in — a global initiative comprising the Software Carpentry, Data Carpentry, and Library Carpentry communities. These communities are dedicated to equipping researchers with essential computational and data science skills, helping them to work smarter, not harder.

Read More
Documentation From User Experience

Documentation From User Experience

This post is a condensed version of a talk at our Data Compentcy College

If you regularly use scientific software written by others, or tried to replicate interesting research that relies on software, you have probably also invested weeks of work to solve a software problem or even given up on a software because of missing documentation. Finding a project that might be the solution to your problem and then failing to run the code is frustrating. Being unable to run a project you have built yourself years ago is even worse. Having experienced all those setbacks myself in the past I want to use this post to channel that frustration to fuel solutions for better documentation for our current and future projects.

Read More