Graduate School

The research area of data assimilation provides excellent research and career opportunities for young researchers. The CRC will support young researchers in their academic career at all stages beginning at the level of Master and PhD studies, continuing with postdoctoral research and leading into an early research career at university level.

The Integrated Research Training Group will provide in particular a structured training and career support program, which will allow PhD students to fully utilize the potential of the CRC for early career development.

This term the RingVL will take place every. Each Thursday from 14:15-17:45 one project will give you some insights into basic concepts of their work. Exercises will take place on Mondays from 16:15 -17:45. You can find on overview here.

Data assimilation is a fascinating and challenging mathematical research field with a broad range of important applications. The integrated Research Training Group (RTG) will provide the coordinated study program for the doctoral students of the SFB 1294. The educational goal is to train young researchers in the field of data assimilation and to enable them to carry out research at the interface of applied and computational mathematics, statistics, probability theory and machine learning.

At the same time, students will be enabled to apply advanced mathematical techniques to data assimilation problems of practical relevance. Besides an excellent technical competence, the RTG conveys interdisciplinary skills and establishes a common scientific basis for its researchers. It will facilitate integration into the international scientific community and its members will become independent, broad minded and responsible scientists who are able to pursue promising careers in science and industry.

The training program of the RTG comprises the following key elements:

  • kick-of camp at the start of the CRC
  • first year courses 
  • annual RTG Jamboree
  • regular CRC research seminars
  • annual summer/winter school
  • professional skills training courses and certification programs

Our doctoral researchers will be supervised by two members of the CRC. Two cohort mentors will provide additional career development advice, will coordinate common activities of the RTG, and will oversee the overall development of our doctoral researchers.

To strengthen the autonomy of our doctoral researchers, the RTG will provide a budget which our doctoral researchers will administer themselves. For instance, they may organize informal get-togethers where they can discuss their work. They may also use these funds to organize small workshops according to their interests and needs. 

The CRC makes it a priority to support researchers will family by providing childcare during CRC-related events, by arranging individual support during periods of parental leave, and by enabling flexible working arrangements. 

An introductory seminar to the topic of the colloquia is given before each colloquium from junior scientists - for junior scientists in the lecture hall from 9:00-9:45. Come and join us.


 We will continue the successful start of the Journal Club this term!

The next Journal Club of the winter semester 2018/19 will take place on Friday, the 1st of February at 12.45 pm. Paul Rozdeba and Randolf Altmeyer will organize the meeting, which will take place at campus Golm, building 28, room 0.102. Make sure you join the club to discuss new approaches or refresh the memory of those 'aged' but important papers. This week discussions will focus on the topic talked about by Charlotte Kloft in the colloquium in the morning and focus on the following three papers:

1) Basic concepts of Pharmacokinetic/pharmacodynamic (PK/PD) modelling (Meibohm and Derendorf, 1997)

2) Basic Concepts in Population Modeling, Simulation, and Model-Based Drug Development-Part 2: Introduction to Pharmacokinetic Modeling Methods (Mould and Upton, 2013)

3) Basic Concepts in Population Modeling, Simulation, and Model-Based Drug Development: Part 3-Introduction to Pharmacodynamic Modeling Methods (Upton and Mould, 2014)