HIDA PhD Kick - Off DaysIn-Person Event

19 May 2025, 13:00 → 20 May 2025, 19:00 Europe/Berlin

Berlin

HIDA PhD Kick - Off Days 

Join us for the HIDA PhD Kick-Off Days in our HIDA Hub – an onboarding event tailored to new PhD students from all 6 Helmholtz Information and Data Science Schools:

MUDS, DASHH, MarDATA, HDS-LEE, HEIBRiDS and HIDSS4Health

What to expect

• Get to know HIDA & Helmholtz: Discover the initiatives, platforms, and opportunities offered by HIDA, Helmholtz and the HIDS Schools.
• Build connections: Network with fellow students that started their PhD journey at the same time as you, alumni, and experts across Helmholtz
• Skills Development: Participate in workshops advancing you on your interdisciplinary PhD journey
• PhD Project Showcase: Share your research in small group discussions

Highlights

• Keynotes from a HIDA alumni and data science experts.
• Poster marketplace showcasing HIDS Schools, Helmholtz platforms offers, and career paths.
• Training workshops on cutting-edge topics such as AI Ethics, LLMs, and interdisciplinary collaboration.

 

This 1.5-day event is designed to familiarize you with the HIDA & Helmholtz ecosystem, get to know your fellow Doctoral Researchers at the HIDS Schools, expand your skills, and kickstart your PhD journey

Save the date and join us in building a strong community of data-driven researchers!

Days and Times, Location

Start: 19 May 2025 lunchtime

End: 20 May 2025 afternoon

Helmholtz Information and Data Science Academy

Anna-Louisa-Karsch-Str. 2

10178 Berlin, Germany

Travel arrangements & finances

HIDA will cover the on-site costs, including food & drinks.

Each participant has to make their own travel arrangements.

Registration & Confirmation

Registration will be open as of February 19.

We advise not to make travel arrangements until your registration was confirmed by HIDA, which is scheduled for April 16.

We look forward to seeing you in Berlin!

The HIDA Team

 

Monday 19 May

1 Welcome & Arrival

2 HIDA & the Research School Network: "Welcome to HIDA: Your Gateway to Data Science in Helmholtz"

Get to know the Helmholtz Information & Data Science Academy (HIDA) — Germany’s largest postgraduate training network in information and data science. In this session, the HIDA team will introduce the HIDA PhD LifeCycle, the six Research Schools (MarDATA, MUDS, HDS-LEE, HEIBRiDS, HIDSS4Health, DASHH), and the tools and platforms available to support your research, networking, and communication. Learn how HIDA connects doctoral researchers across disciplines and institutions, and how you can make the most of its diverse opportunities throughout your PhD journey.

3 PhD to What’s Next: Insights from Science and Economy

Two alumni of the HIDA Research Schools share their personal journeys after completing their PhDs: Siddhant Agarwal (HEIBRiDS alumnus, now at Hereon) offers insights into continuing a career in science, while Carola Trahms (MarDATA alumna, now at EvoLogics) reflects on her path into industry. Their short keynote talks will be followed by a joint panel discussion and Q&A, exploring key decisions, challenges, and opportunities when choosing between academia and the private sector. A session full of honest perspectives and valuable takeaways for anyone wondering: What comes after the PhD?

Speakers: Carola Trahms (MarData Alumna, EvoLogics), Siddhant Agarwal (HEIBRIDS almunus, HEREON)

4 Marketplace & Poster Session: Explore the Helmholtz Universe: Platforms, Tools & Opportunities

Grab a coffee and explore the diverse landscape of Helmholtz platforms and initiatives at our interactive Marketplace and Poster Session. Learn more about HIFIS, Helmholtz AI, the Helmholtz Metadata Collaboration, Helmholtz Imaging, and other exciting opportunities at HESIE, the Open Science Office and more. Connect with experts, ask questions, and discover how these services and tools can support your research and collaboration within the Helmholtz ecosystem.

5 Phd Project Pitches

Pitch your research project to your peers and identify your future sparring partners!
We will form small groups and a rotating system to make sure you get a good overview of the (planned) research projects and focus points from your peers.

6 Final discussions

Tuesday 20 May

7 Arrival at HIDA Hub

8 Welcome & Agenda of the day

9 HIDS School Networking Session

10 Workshop 1: LLMs in Practice: Using AI Tools Wisely in Research Software Engineering

You might already be using Large Language Models (LLMs) to write code, debug, or even brainstorm research ideas. But how do these AI tools fit into the bigger picture of good scientific practice?
This workshop is your guide to understanding the role of LLMs in Research Software Engineering. We'll explore how they can help you iterate on code faster, improve documentation, and navigate tedious programming tasks—but also look closely at the risks, such as incorrect outputs, hidden biases, and unclear contributorship. In addition, we'll connect these tools to research integrity: What does “responsible use” really mean? How can you use LLMs while staying transparent, reproducible and in line with research integrity?
With practical examples, interactive exercises, and discussions, this session will raise awareness for using LLMs effectively and responsibly when working on research software.

PLEASE BRING YOUR LAPTOP!

Speakers: Jan Ebert (FZJ), Katrin Frisch (Ombuds Committee for Research Integrity in Germany)

11 LUNCH

12 Workshop 2: Model Cards for Scientific Machine Learning: Transparency, Accountability, and the Future of Documentation

As machine learning becomes central to scientific discovery—from neuroscience to climate modeling—new tools are needed to document models in ways that support transparency, replicability, and responsible reuse. Model cards offer a structured format for reporting how an ML model works, where it performs well (or poorly), and what limitations or risks it carries. Originally proposed to address fairness in commercial AI, model cards are now being adapted for scientific settings, where openness and rigor are equally essential.

In this seminar, we explore how model cards can support not only ethical reflection but also scientific clarity. We will compare them to traditional methods sections, examine real examples (including from biomedical AI), and critically evaluate when—and how—model cards should be written. Participants will also create their own mini-model card sketches, and we’ll close by considering how these tools might evolve in the context of large foundation models and domain-specific scientific norms.

This seminar is ideal for early-career researchers using ML in the sciences, especially those interested in reproducibility, interpretability, and responsible deployment.

Speaker: Charles Rathkopf (FZJ)

13 Workshop 3: Interdisciplinary Collaboration

Interdisciplinary collaborations are often the most efficient route to managing complex research questions because they are integrative and benefit from collective expertise. However, such research requires effective communication across boundaries. Collaborators often have vastly different approaches to research design and methodology, and different technical vocabularies and communication cultures.
Successful communication in interdisciplinary settings requires the ability to express your research in ways that are clear and understandable to others outside of your discipline or expertise. With a few fundamental strategies for communication and presentation it is possible to illustrate complex information in a context relevant way, to convince others, to win supporters and thus reach the respectively set goals.
In this workshop the participants sharpen their personal communication strategies to engage in constructive collaborations in interdisciplinary settings. The workshop contents include:
- Communication & presentation basics: Clear goals und a thorough preparation
- Go public – go scientific! Coordinating the joint effort
- Everything under control? Dealing with difficult situations
- Interdisciplinary cooperation: My next steps

Speaker: Cornelia Altenburg (Golin Wissenschaftsmanagement, Berlin)

14 Final discussions & Good Bye