Research Assistant in Machine Learning (2 Positions): Join the dynamic team at Technische Universität Berlin as a Research Assistant in Machine Learning. This position involves conducting research in the field of Machine Learning, with a focus on developing analysis methods for nonstationary data. If you have a background in Mathematics or Computer Sciences, expertise in statistical learning theory and machine learning methods, and a passion for advancing robust statistical learning solutions, we invite you to apply.
Designation: Research Assistant
Research Area: Machine Learning
Location: Technische Universität Berlin, Germany
Eligibility/Qualification:
- Master’s, Diploma, or equivalent degree in Mathematics or Computer Sciences or a comparable field
- Several years of experience as a scientific research assistant in the field of machine learning (desirable)
- Extensive knowledge of statistical learning theory, machine learning methods, kernel methods, neural networks, probability theory, statistics (Bayes‘ statistics, Bayes‘ optimization, variational methods, etc.)
- Proficiency in programming (Python or Matlab) and object-oriented languages (Java or C++)
- Experience in applying machine learning methods to high-dimensional data (regression, classification, clustering) and their empirical evaluation
- Good teaching skills in German and/or English
Job Description:
- Conduct research in Machine Learning, with a focus on nonstationary data
- Develop robust methods to solve statistical learning problems
- Perform statistical analysis of multi-dimensional data
- Implement, apply, and evaluate machine learning techniques in various scientific domains (medical data, quantum chemistry, etc.)
- Supervise bachelor/master students
- Fulfill teaching duties in the subject area
How to Apply: Submit your application with the reference number (IV-551/23) via mail or email to:
- By post: Technische Universität Berlin, Die Präsidentin, Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Müller, MAR 4-1, Marchstr. 23, 10587 Berlin
- By email (one PDF-file, max. 5 MB): sekr@ml.tu-berlin.de
Application Deadline: 15 January 2024
Disclaimer: This job post is based on information from a reliable source. Applicants are advised to verify details from the official Technische Universität Berlin website for the most accurate and up-to-date information.
