About us:

Our team of highly motivated and aspiring researchers, led by Prof. Stefan Feuerriegel, is based in Munich.

We are particularly interested in developing new methods. Our research is driven by the strong desire to conquer the grand challenges of our society:

• Bringing AI into healthcare
• Curbing fake news with AI tools
• Fighting the coronavirus epidemic with data-driven insights
• Automating marketing with AI
• Developing new tools for “AI for Good”

For this purpose, we draw upon recent advances in artificial intelligence and statistical modeling to produce actionable insights. In our research, we develop new AI methods, often inspired by real-world applications.

We have partnered with leading institutions like the World Health Organization, the OECD, and leading industry players to develop new state-of-the-art tools for management that are powered by AI. We further aim to publish in top-tier outlets from applied AI (e.g., KDD, WWW). We are also open to more outlets in technical AI (e.g., AISTATS, ICML), statistics, or management (e.g., Marketing Science, Operations Research).

Please visit our website for further information about us.

We are looking for you:

Research and Teaching Assistant (PhD Candidate) in Applied Artificial Intelligence (m/f/x)

in Munich

Your tasks and responsibilities:

As part of the team candidates have to be highly self-motivated to perform creative and independent research.

Candidates will also gain experience in teaching undergraduate and graduate courses and seminars, and support students in thesis work.

Your qualifications:

Ideally, the candidate has a master’s degree in mathematics, applied mathematics, statistics, computer science, or business informatics (or a related field). Fluency in English is required. Work is almost entirely research-centered with limited teaching duties.

A suitable candidate will be interested in one (or more) of the following topics:

• Causal machine learning
• Machine learning, deep learning, artificial intelligence
• Probabilistic machine learning (hidden Markov models, Hawkes processes)
• Bayesian learning (MCMC, Gaussian processes, variational inferences)
• Policy learning
• Statistics (Bayes)

Topic-wise our research group is always open to own proposals and further suggestions.

Benefits:

You will be in a motivated team with a very vibrant atmosphere. Our offices are in central Munich. During this time, participation in conferences and voluntary exchange programs are also supported. Past graduates have landed top positions in both industry and academia (e.g., University of Oxford). We work with an international network of researchers (e.g., Harvard, Yale, NYU, Cambridge) to develop solutions for today’s and tomorrow’s global challenges.

The position is initially for one year with an option to extend until the end of the PhD. The starting date can be set individually, as preferred by the candidate.

We encourage women to apply.

Also possible in a part-time capacity.

Contact:

We look forward to receiving your online application. We have a lightweight application procedure (CV and transcript only) to minimize effort on both sides. Cover letter or internship reports are not required. Please note that we only accept applications submitted via e-mail to ai@som.lmu.de no later than 10.05.2024.

Where knowledge is everything.

LMU researchers work at the highest level on the great questions affecting people, society, culture, the environment and technology — supported by experts in administration, IT and tech. Become part of LMU Munich!