Regulations for the Program

The Joint Committee with decision-making power for the International Master’s Program in Computational Neuroscience has issued the following Study, Examination and Admission Regulations for the joint International Master’s program at the Berlin Institute of Technology and Humboldt-Universität zu Berlin. The German versions are official and legally binding (see below).

The responsible administrative bodies of the university are:

Admission Regulations (EN) / Zulassungsordnung (DE)

Study Regulations (EN) / Studienordnung (DE)

Examination Regulations (EN) / Prüfungsordnung (DE)

Committees

There are two committees and one board associated with the Master program. The Joint Committee (GKmE) is responsible for processes, such as enacting legal regulations and the curriculum of the program. The Study Committee is responsible for the content of the studies. The Examination Board is responsible for all examination matters.

The Joint Committee consists of 4 full professors from each of the participating faculties, 1 academic/scientific employee, 1 student, and 1 member of non academic staff, as well as their respective deputies.

 

Joint Committee (GKmE)
Professors Academic staff
  substitute:
Klaus Obermayer (Head, TU) Manfred Opper (TU)
Richard Kempter (vice-head, HU) Bernhard Ronacher (HU)
Martin Paul Nawrot (FU) Stephan Sigrist (FU)
John-Dylan Haynes (Charité) Andreas Heinz (Charité)
  substitute:
Owen Mackwood (HU) Michael Schmuker (FU)
Students Non academic staff
  substitute:
Natalie Schaworonkow (TU) Katja Müller (TU)
  substitute:
Margret Franke (HU) Katrin Schulze (Charité)
Contributors: Robert Martin (Charité), Vanessa Casagrande (TU), Julia Schaeffer (HU)

The Examination Board consists of 3 full professors, 1 academic/scientific employee and 1 student of the program as well as their substitutes. The Examination Board will be responsible for all questions relating to the Examination Regulations as well as for all resulting tasks and decisions in examination matters, in particular for

  • the organization of the examinations, e.g. repetitions of exams
  • the recognition of study and examination achievements,
  • the preparation of lists of examiners and associate examiners,
  • the decision on equivalent study or examination achievements for students who, due to physical handicap or impairment, are not able to provide study and examination achievements in the required form.
  • the allocation of a master thesis topic after consultation with the student who can make a suggestion

 

Examination Board
Professors Academic Staff
  substitute:
Benjamin Lindner (HU, head) Wilhelm Stannat (TU)
Michael Brecht (HU, vice head)
Benjamin Blankertz (TU)
  substitute:
Robert Martin (Charite) Audrey Houillon (TU)
Students
  substitute:
Christian Donner (TU) Ivana Kajic (TU)

 The Study Committee consists of 1 full professor and his/her substitute, 1 academic/scientific staff and his/her substitute, and two students.

Credits

The workload of the program is measured in credit points based on the European Credit Transfer and Accumulation System (ECTS). The general rule is that 30 hours of student invested time make up 1 credit point. These hours can be made up of class time as well as time to prepare for or recap classes. Credits can be accrued by lectures, tutorials, praticals, seminars and projects.

Students in the MSc program need to accrue 120 credits in total, with 20 credits included for the Master thesis. These credits are divided into the 10 modules as shown in the table.

Models of Neural Systems
12 LP
Acquisition and Analysis of Neuronal Data
12 LP
Machine Intelligence
12 LP
Programming Course and Project
6 LP
Individual Studies
6 LP
1st
year
Models of Higher Brain Functions
12 LP
Lab Rotations (Three Projects)
3x9 LP
Ethical Issues
3 LP
2nd
year
Courses on Advanced Topics
10 LP
Master Thesis
20 LP

Grading system

The grading system ranges from 1.0 to 5.0 with 1.0 being the best grade and 5.0 the worst. 4.0 is the minimum grade for passing. A detailed description of individual grades can be found in the table below.

grade assessment definition
1.0 / 1.3 Sehr Gut (Very Good) excellent achievement
1.7 / 2.0 / 2.3 Gut (Good) achievement, which is considerably above
2.7 / 3.0 / 3.3 Befriedigend (Satisfactory) achievement, which in every respect meets
average requirements
3.7 / 4.0 Ausreichend (Fair) achievement, which – despite deficiencies – still meets the requirements
5.0 Nicht ausreichend (Unsatisfactory) achievement with considerable deficiencies, which does not meet the requirements

Examinations

Each module is concluded by a final examination. There are three different types of examinations:

  • oral examination
  • written examination
  • study achievements equivalent to the examination

Currently only two types of examinations are employed:

  • oral exminations
    • Models of Neural Systems
    • Models of Higher Brain Functions
    • Acquisition and Analysis of Neural Data
    • Machine Intelligence
  • study achievements equivalent to the examination
    • Programming Course and Project
    • Lab Rotations
    • Ethical Issues and Implications for Society
  • The examinations for the optional modules
    • Individual Studies
    • Courses on Advanced Topics
    are determined by the person responsible for the module.