Max Planck Institute for Intelligent Systems has a newly established Minerva Research Group on Probabilistic Learning, headed by Isabel Valera, within the Department of Empirical Inference, and is inviting applications for PhD students in the area of machine learning, particularly in Bayesian modeling and inference, starting early 2019.
About the position:
- The probabilistic learning group has extensive work on Bayesian modeling and inference on real-world data such as heterogeneous and continuous- and discrete-time data, automating data pre-processing, exploratory data analysis and fairness in ML; and covers diverse applications domains which range from bioengineering and psychiatry to social and communication systems.
Requirements:
- Applicant must hold a Master’s degree in mathematics, computer sciences, statistics or related subjects, and with a strong background in probability theory and statistics, as well as good programming skills.
- Knowledge in machine learning is helpful, but not mandatory.
Funding duration: contract (initially for three years)
Applications:
- Apply online and must include the following:
- CV
- Research statement (1-2 page)
- List of at least 3 references
- Scanned transcripts
- Important papers (if available), major/internship reports (if available) and last thesis abstract (if available).
Job Code: is_w001
—————–Quick Overview————- | |
Organization | MPI for Intelligent Systems |
Country | Germany |
Fellowship Level | Doctoral |
Subject areas | Mathematics, Computer Sciences, Statistics |
Fellowship amount | Funded for 3 years |
Eligibility | Open to all nationalities |
Deadline | August 20th, 2018 |
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