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UM-Bridge Workshop 2024, Dec 5/6

Online workshop on UM-Bridge, a language-agnostic interface linking Uncertainty Quantification (UQ) packages and numerical model software.

Registration deadline: November 24

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Call for proposals (KIT internal): DAAD Graduate School Scholarships at KCDS

We are calling researcher tandems (MATH and SEE) at KIT to submit interdisciplinary project ideas!

Deadline: January 31, 2025

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Career Talk with KIT Alumni: From Computational and Data Science to Industry and Academia (Oct 11, 2024)

Wondering whether to choose academia or industry for your next career step? Join us for a panel discussion with KIT alumni sharing their experiences, job profiles, and career journeys in computational and data science.

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Upcoming events

 
Lecture

"Explainable AI: How Is It Made, and What's at Stake?" - KCDS Talks - November 2024

Friday, 29 November 2024, 16:00-17:30
Hybrid: TRIANGEL Studio @Kronenplatz and Zoom

Zoom Link

The KIT Graduate School Computational and Data Science (KCDS) at KIT Center MathSEE is excited to invite you to the upcoming KCDS Talk, part of our monthly series covering a broad spectrum of topics from fundamental concepts to current trends in computational and data science.

 

In November, we are pleased to welcome two distinguished speakers:

 

  • Dr. Michael Poznic (Philosophy of Engineering, Technology Assessment & Science, KIT ITAS)
  • Dr. Nadia Burkart (Applied Explainable AI, Fraunhofer IOSB)

 

Under the heading "Explainable AI: How Is It Made, and What's at Stake?" the two individual talks will delve into the development and application of explainable AI (XAI) technologies from different perspectives. As AI becomes more integrated into critical sectors like healthcare, finance, and public services, ensuring that AI decisions are understandable to humans has become a growing priority. This session will explore the philosophical and practical dimensions of XAI, shedding light on the ethical, technical, and societal implications of developing transparent and accountable AI systems.

 

Following the two talks, there will be a discussion with the speakers, offering attendees the opportunity to ask questions and engage in conversation about the topic. The session will be hosted by Lilly Osburg.

 

Snacks and Drinks & Networking Opportunity: After the event, there will be food provided, offering an excellent opportunity to network with the speakers and other attendees. Make the most of this chance to connect and discuss ideas with fellow researchers and professionals.

 

Whether you're a master’s student, a doctoral researcher, a senior academic, or simply curious about the field of AI and its impact, this event promises to offer valuable insights.

 

Join us in person or via Zoom – the event is free and open to all without prior registration.

Speaker
Dr. Nadia Burkart, Dr. Michael Poznic

KIT
Organizer
Angela Hühnerfuß
KIT Graduate School Computational and Data Science (KCDS)
KIT-Center MathSEE
Karlsruhe
Mail: kcds does-not-exist.kit edu
https://www.kcds.kit.edu

Highlights

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The workshop with Dr. Annika Oertel (IMKTRO) and Dr. Vandana Jha (SCC) took place from September 11-12, 2024 at the Mathematics building.

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The first KCDS Summer School centered on the topic of Stochastic and Hybrid Modelling and took place at KIT Campus South, September 18-20, 2023.

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About KCDS

Concept of the graduate school KCDS
KIT Graduate School Computational and Data Science (KCDS) is a graduate school at KIT Center MathSEE that offers an interdisciplinary training program for doctoral researchers in the field of model-driven and data-driven computational science.
In this unique program, doctoral researchers will be able to conduct an interdisciplinary research project that revolves around computational methods such as mathematical models, simulation methods and data science techniques, all the while building bridges between mathematical sciences and an applied SEE discipline (science, economics and engineering).
Addressing global challenges, the school provides a wide variety of topics, from meteorological ensemble forecasting to machine learning in elementary particle physics.
At KCDS, doctoral researchers have one supervisor from the mathematical sciences and one from the applied discipline. They are part of a dynamic community and participate in the school’s interdisciplinary training program, including hands-on training in small groups, summer schools, networking events and hackathons/datathons.
Thinking simulations and data together, we are ready to conquer the data-driven challenges of tomorrow!

Coordination Office