Job
In this role, you will develop innovative methods in machine learning and promote their practical applications for decision-making processes in areas such as medicine and sustainability.
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Your role in the team
- We are seeking highly motivated candidates with a passion for research and a drive to make groundbreaking contributions in the field of AI.
- Research outlook is a top priority for the position.
- Candidates will also gain experience in teaching at the undergraduate and/or graduate level and may supervise student theses.
- Generally, PhD students can pursue either (A) a method track or (B) an application track (or a combination thereof).
- In the (A) method track, the aim is to make contributions to top-tier ML/AI venues (e.g., NeurIPS, ICML, AISTATS, KDD).
- Here, we typically focus broadly on methods around causal machine learning.
- This includes (but is not limited to): causal machine learning, causal representation learning, reinforcement learning, off-policy evaluation/learning, probabilistic ML / uncertainty quantification (e.g., diffusion models, Bayes).
- In the (B) application track, we aim to advance decision-making through new AI/ML tools across various application areas (e.g., sustainability, medicine, marketing).
- Here, PhD students regularly publish in various high-impact outlets (e.g., Nature Communications, Nature Medicine, Management Science, KDD).
- If desired, PhD students can actively collaborate with partners (e.g., Harvard Medical School, Cambridge Centre for AI in Medicine) to solve the major challenges of our time.
- The focus is on demonstrating the value created by new AI/ML tools and applying them in practice.
- This includes: AI/ML for better decision-making in medicine, AI for Good to promote sustainable development, AI/ML for business decision-making, Human-AI collaboration.
- Our research group is always open to independent research proposals and further suggestions.
Our expectations of you
Education
- The candidate has a Master's degree in one of the following subjects: Mathematics, Statistics, Computer Science, Data Science, Machine Learning.
Qualifications
- Our team language is English, so fluency in English is required.
What we offer
- You will be part of a motivated, international team with a very vibrant atmosphere.
- Our offices are in central Munich.
- During this time, participation in conferences, summer schools, and voluntary exchange programs is also supported.
- Work is almost entirely research-centered with limited teaching duties.
- 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.
- It is common for successful candidates to visit our international network for research stays at their premises.
- Past graduates have landed top positions in both industry (e.g., BCG, startups with multi-million seed funding) and academia (e.g., University of Oxford, ETH Zurich).
- The position is initially for two years, with an option to extend until the end of the PhD.
- The starting date can be set individually, based on mutual agreement.
- LMU Munich is an equal opportunity employer, committed to enhancing the diversity of its faculty.
- We encourage female candidates to apply.
- Also possible in a part-time capacity.
- People with disabilities who are equally as qualified as other applicants will receive preferential treatment.
Benefits
Health, fitness & fun
Work-Life-Integration
Topics you will work on
Job locations
About your employer
The Ludwig-Maximilians-Universität München (LMU) is one of the most prestigious and largest universities in Germany. With its outstanding research and teaching, it is a top destination for students from all over the world.
- 250+ Employees
- Established Company
- Hybrid, Onsite
- Education System
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