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• M.Sc. // Statistical physics meets medical diagnostics

  For master students of theoretical physics, applied mathematics, statistics, or equivalent:

  The Data Science group explores the extent to which medical information acquired from photonic data can be utilized in medical diagnostics, personalized health monitoring, and life sciences. Among other topics, we investigate fundamental problems in medical decision-making from both a theoretical and data-driven point of view. Using ideas and tools from information theory, decision theory, as well as statistical physics, we aim for the quantification of medically relevant information carried by different types of health data sets.

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  We have an opening for a master thesis for performing research towards new strategies for improving current medical diagnostic approaches. The project will focus on the development of probabilistic models that lead to precise definitions of disease states as well as their dynamics and interactions. To this end, ideas and methods from statistical physics, machine learning, and inference algorithms will be employed. The resulting models, will be applied and tested on health-related data sets collected in the framework of clinical research studies performed by the University of Munich (LMU) and the Center for Molecular Fingerprinting (CMF).

  Required qualifications:

  1. Experience with programing in Python or equivalent;
  2. Good knowledge of probability theory and statistical physics;
  3. Very good academic record;
  4. Interest in medical applications .

  If interested, please get in touch with Dr. Kosmas Kepesidis (kosmas.kepesidis@physik.uni-muenchen.de) and Lea Gigou (lea.gigou@physik.uni-muenchen.de) to discuss this possibility. Our group is based at the Research Center in Garching (Forschungszentrum Garching, Section Physics of LMU, Am Coulombwall 1, 85748 Garching), which is easily accessible by public transport.

  Contact:

  Dr. Kosmas Kepesidis
  kosmas.kepesidis@physik.uni-muenchen.de
  Lea Gigou
  lea.gigou@physik.uni-muenchen.de

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• M.Sc. // Data engineering and analytics

  For master students of computer science, data science, information technology, or similar:
      
  The Data Science group explores the extent to which medical information acquired from photonic data can be utilized in medical diagnostics, personalized health monitoring, and life sciences. To this end, we investigate relevant procedures for experimental and study design as well as data management and pre-processing. We combine these procedures with machine learning methods and ideas from medical statistics in appropriate data-science pipelines. 

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  We have an opening for a master thesis project for performing research towards best practices for collecting, storing, and analyzing scientific (health-related) data at scale. Such data are from multiple sources and formats that range from clinical and laboratory data to fingerprinting measurements of human blood. This involves appropriate database design and management, and the development of unified domain-specific data-science pipelines for data processing and analysis.

  Required qualifications:

  1. Experience with programing in Python or equivalent;
  2. Experience with relational databases ;
  3. Familiarity with analytics and data mining techniques;
  4. Interest in medical applications.

  If interested, please get in touch with Dr. Kosmas Kepesidis to discuss this possibility. Our group is based at the Research Center in Garching (Forschungszentrum Garching, Section Physics of LMU, Am Coulombwall 1, 85748 Garching), which is easily accessible by public transport.

  Contact:

  Dr. Kosmas Kepesidis
  kosmas.kepesidis@physik.uni-muenchen.de
  

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