Job
In dieser Position entwickelst du innovative Methoden im Bereich des maschinellen Lernens und förderst deren praktische Anwendungen für Entscheidungsprozesse in verschiedenen Bereichen wie Medizin und Nachhaltigkeit.
Deine Rolle im 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 the top-tier outlets from ML/AI (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 collaborate actively with partners (e.g., Harvard Medical School, Cambridge Centre for AI in Medicine) to solve the big problems of time.
- The focus is to show the value created by new AI/ML tools and to apply 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 own research proposals and further suggestions.
Unsere Erwartungen an dich
Ausbildung
- The candidate has a Master's degree in one of the following subjects: Mathematics, Statistics, Computer Science, Data Science, Machine Learning.
Qualifikationen
- Our team language is English, so fluency in English is required.
Unser Angebot
- You will be in 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 are 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
Gesundheit, Fitness & Fun
Work-Life-Integration
Themen, mit denen du dich im Job beschäftigst
Job-Standorte
Das ist dein Arbeitgeber
Die Ludwig-Maximilians-Universität München ist eine der angesehensten Universitäten in Deutschland. Durch ihre hervorragenden Forschungseinrichtungen und das breite Studienangebot zählt sie zu den größten Universitäten des Landes.
- 250+ Mitarbeitende
- Etablierte Firma
- Hybrid, Onsite
- Bildungswesen
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