Jakob Runge

Jobs Current open positions appear here. Junior / Senior AI Research Consultant (2 Positions) – AI.UP The AI Competence Center (AI.UP) at the University of Potsdam invites applications for two AI Resear…

We’re hiring 2 AI Research Consultants (Junior/Senior) at the University of Potsdam (AI.UP).

TV-L E13 (100%), 4 years.
Focus: interdisciplinary AI consulting and independent research.
Deadline: March 22, 2026
Details: causalinferencelab.com/jobs

Jobs Current open positions appear here. Junior / Senior AI Research Consultant (2 Positions) – AI.UP The AI Competence Center (AI.UP) at the University of Potsdam invites applications for two AI Resear…

Hiring! Postdoc in Causal Inference & Explainable AI at University of Potsdam (CRC 1294 “Data Assimilation”).
TV-L E13 (100%), until 06/2029. Start summer 2026.
Deadline: March 22, 2026.
Apply (ID 308/2026): lisa.goesel@uni-potsdam.de
Details: causalinferencelab.com/jobs

Jakob Runge: Causal Inference on Time Series Data with the Tigramite Package YouTube video by Online Causal Inference Seminar

Here's a recent intro talk on the Tigramite python package for causal inference on time series data (also works on non-time series):
www.youtube.com/watch?v=DZbL...

Github: github.com/jakobrunge/t...

Part of the great Online Causal Inference Seminar series:
sites.google.com/view/ocis/home

Climate Informatics An open community at the intersection of climate science and data science.

Save the date! 🌍

Climate Informatics will convene researchers at the intersection of weather & climate science, statistics, and machine learning, April 27-30, 2026 on our beautiful UNIL/EPFL campus by Lake Geneva in Lausanne, Switzerland.

More info: climateinformatics.org

CAR Causal Abstractions and RepresentationsWorkshop @ UAI 2025July 25th 2025, Rio de Janeiro 🇧🇷

🎉 The first edition of the "Causal Abstractions and Representations" workshop is here!

🇧🇷 Proudly hosted by @auai.org, we'll be in Rio de Janeiro on July 25, 2025.

🔨 Check out our invited speakers and the call for papers: we can't wait to see your submissions!

🌐 sites.google.com/view/car-25/

tigramite/tutorials/causal_discovery/tigramite_tutorial_pairwise_mult_ci.ipynb at master · jakobrunge/tigramite Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at - jakobrunge/tigramite

Got multivariate X and/or Y and want to test conditional independence X _|_ Y | Z ? PairwiseMultCI is a wrapper that turns any univariate CI test into a multivariate one... it can also help increase power!
Tigramite tutorial github.com/jakobrunge/t... UAI Paper proceedings.mlr.press/v216/hochspr...

tigramite/tutorials/causal_discovery/tigramite_tutorial_heteroskedastic_ParCorrWLS.ipynb at master · jakobrunge/tigramite Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at - jakobrunge/tigramite

Causal discovery loves conditional independence tests -- here's our CI test of the month: ParCorrWLS can deal with heteroskedastic data! Tigramite tutorial: github.com/jakobrunge/t... NeurIPS paper: proceedings.neurips.cc/paper_files/...

Hello BlueSky! This is the start of my new timeline, gradually moving away from X/Twitter. Thanks for following! I will share new work here and look forward to exchanging ideas on causal inference for time series data with you!

Bagged-PCMCI+ is out! A bootstrap approach to enhance precision+recall and confidence quantification for causal links. Check out our CLeaR paper: https://rb.gy/6t5gba and tigramite tutorial: https://rb.gy/db9ro1 #CLeaR2024 @ELLISforEurope @ERC_Research @KDebeire

Contribute to the 2nd workshop on causal inference for time series at UAI, this year on July 19 in Barcelona! Deadline for submissions is May 19, less than 10 days to go! Looking forward to another successful event! Details: https://sites.google.com/view/ci4ts2024/home #CI4TS #UAI2024

Got causal questions and multiple datasets collected for different contexts/conditions/subjects/locations? Try J-PCMCI+, a causal discovery method for multiple time-series datasets, able to handle both observed and latent context-confounding! https://proceedings.mlr.press/v216/gunther23a.html

How do you choose you pet friend in the zoo of causal inference methods? Our recent JMLR paper provides a comprehensive benchmark comparison for the bivariate cause-effect challenge: https://www.jmlr.org/papers/v24/22-0151.html. For this and many more benchmarks visit http://causeme.net!

A view-only version can be found here: https://rdcu.be/dfs5X

3/3 Another highlight: A decision diagram to find the right approach for your problem. Great joint work with Andreas Gerhardus, Gherardo Varando, Veronika Eyring, and Gustau Camps-Valls. Integrate causal thinking into your #MachineLearning data-driven science!

1/3 Just published @NatRevEarthEnv https://tinyurl.com/3zb8cu7s. A guide to #causalinference for time series: Phrase your problem as a causal Question, transparently state Assumptions, and apply the right method on your Data with the QAD-template based on @yudapearl's causal hierarchy

Causality in Data Science – Medium In this blog researchers and practitioners from the causal inference research group at the german aerospace center publish easy to read blog articles that should give an introduction to the topics of causal inference in machine learning.

Looking for a gentle introduction to #causalinference and relations to #MachineLearning learning? Kenneth Styppa heads a blog series of our group at https://medium.com/causality-in-data-science

We are hiring a scientific programmer (German E13 salary) in Jena to support tigramite and other software projects! Interested? More on https://climateinformaticslab.com/jobs/

To all (too)late-submitters: We extended the paper deadline by a few days, it is now June 03 11:59AM UTC-0 !

Few days left to submit to our UAI workshop on causal inference for time series data!

Happy to announce a workshop on causal inference for time series data at @UncertaintyInAI in August this year, together with @saramagliacane @ckassaad @JonasChoice and others! Including a Call4Papers 👉 https://sites.google.com/view/ci4ts2023

Great to be attending @Climformatics in lovely Cambridge! Congratulations to the organisers for setting it up so well! https://twitter.com/Climformatics/status/1648607027671834624

Join the Causal Inference Lab! Open #postdoc position on developing #causality methods for a range of application domains! --> http://climateinformaticslab.com @DLRdatascience @ELLISforEurope @ERC_Research

2/2 The paper also introduces Mapped-PCMCI, a spatio-temporal causal discovery method to reconstruct causal networks from gridded data: Going from correlation to causal networks utilizing the assumption of a lower-dimensional latent causal process.

1/2: We just published a paper in @EnvDataScience where we present the SAVAR model, a spatiotemporal toy model for benchmarking causal inference methods. Congratulations to Xavi Tibau! And now time to test your causal methods! https://bit.ly/3LQA7zh

PS: We now have *flexible home office rules* at DLR enabling you to partially also work from another city than Jena.

**Join the Causal Inference and Climate Informatics Lab!**
We are expanding with 4 open #postdoc positions (#phd also possible) on developing #causality theory and methods for #EarthSciences and beyond!
👉 http://climateinformaticslab.com
@DLRdatascience @ELLISforEurope @ERC_Research

2/2 Interested to develop #Causality and #AI theory and methods and work with climate scientists to better understand climate change and extremes? Join our team at http://climateinformaticslab.com

What are the causes behind recent extreme floods? Coming from math/stats/physics/ML and want to develop #Causality and #AI theory and methods to better understand extremes? --> Open positions with @ZscheischlerJak and further collaborators: http://climateinformaticslab.com @Compound_Event

Got a background in math/stats/physics/ML and want to work on #Causality and #AI inspired by challenges in #EarthSciences and #ClimateChange? --> Well-funded #Postdoc/#PhD posts at @TUBerlin and @DLR_en Jena! --> http://climateinformaticslab.com @ELLISforEurope @ERC_Research

The ClimateInformaticsLab starts a new branch at @TUBerlin as part of my ERC Starting Grant #CausalEarth. We have two upcoming #Postdoc/#PhD positions in #Berlin on #Causality and #AI for #Earth sciences. More info: https://climateinformaticslab.com @ELLISforEurope @ERC_Research @EU_H2020