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

Firma: Ludwig-Maximilians-Universität München

Arbeitsort / Location: München, Bayern

Job Beschreibung: Ludwig-Maximilians-Universität München is a leading research university in Europe. Since its founding in 1472 it has been committed to the highest international standards of excellence in research and teaching.

Institution Faculty of Business Administration – Munich School of Management – Faculty of Mathematics, Computer Science and Statistics – Institute of AI in Management

Remuneration group TV-L E13

Full-time / Part-time Full-time (100%)

Start date as soon as possible

Application deadline 2023-08-31

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 .

We are looking for you:

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

in Munich

Your tasks and responsibilities:

You will be part of our AI research team and work in a very vibrant atmosphere in our offices in 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.

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

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.

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:

The application of women is welcome.

Also possible in a part-time capacity. People with disabilities who are equally as qualified as other applicants will receive preferential treatment.

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 email to no later than 31.08.2023.

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.

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