The Bernstein Center for Computational Neuroscience Berlin (BCCN) is a leading research institution which hosts a number of groups working on questions related to neural computation from the single cell level all the way to the systemic level, both theoretically and experimentally. It hosts a Master and a PhD program to combine outstanding research with excellent teaching.
Neuroscience is one of the most rapidly developing and most important sciences of the 21st century. Understanding the functioning of the brain requires the collaborative efforts of neurobiologists, psychologists, cognitive scientists, medical researchers, computer scientists, mathematicians, physicists and engineers. A deeper insight into the functioning of the brain can be gained only through a research methodology that integrates computational modeling with empirical neuroscience. This integration is the basis of daily research work at the BCCN. Besides its focus on theory / experiment interactions, the BCCN Berlin has put major emphasis on conducting and pursuing research in an international context.
Internationality is ensured by worldwide collaborations, the presence of principal investigators with an international track record, and an international Bernstein Master and Doctoral program that attracts students from all over the world. There is no long-term prospect in science without the recruitment and education of young scientists. Benefiting from high commitment on part of the whole scientific staff, the Bernstein Center has become the cradle of intense teaching activity aimed to offer an excellent scientific training to selected outstanding students.
A faculty composed of principal investigators with complementary expertises grants the students an interdisciplinary education with the goal of empowering them to communicate across the diverse disciplines and to make their own contribution to the fast growing field of neuroscience. The structure of the teaching modules reflects the fundamental principle of theory/experiments integration: Each module is composed of a theoretical lecture complemented by analytical and programming tutorials as well as practical courses in the lab. Established in 2006/2007, the two graduate programs are growing more and more popular, as it is witnessed by the increasing number, quality, and internationality of the received applications.
Research at the BCCN Berlin addresses one of the most challenging questions in computational and cognitive neuroscience:
How is it possible that we can process sensory stimuli with millisecond precision and initiate appropriately timed motor behavior if intermediate processing elements - on the level of single synapses, single neurons, small networks and even large neural systems - vary significantly in their response to the same repeated stimulus?
This question is investigated in different research projects which are articulated in two main branches: The cellular branch, which focuses on discharge patterning and variability, and the cognitive branch which pursues computational approaches to prediction in human neuroscience and cognition. In the past years, the BCCN Berlin has produced major scientific results which have critically altered the thinking about "Precision and Variability" in the nervous system. Among other achievements, BCCN researchers have gained new insights into the computational role of individual neurons in large neural networks (such as the rodent nervous system), have contributed to understanding how the brain achieves its remarkable perceptual stability despite large variability at the level of the sensory signal, have demonstrated that brain signals may carry information about human decisions long before subjects are actually aware of their respective decision.
Addressing such questions requires a multi-scale interdisciplinary approach, the exploitation of different brain-imaging techniques and a constructive exchange between experiments and modeling: This becomes possible thanks to the infrastructure and the facilities of the BCCN Berlin.
Closely related to the Bernstein Center, this Training Group funded by the German Research Council provides scholarships for doctoral students and features a scientific program focused on sensory coding and perception. Since perception is task dependent (perception serves a purpose), sensory processing is connected to cognitive functions (decision making, memory function, planning, and even motor control) and has to be linked to performance measures. The goal of the Research Training Group is to exploit new ideas from the machine learning field to develop theoretical concepts for specifically addressing temporally varying inputs, coding strategies for stimulus time series, and computation with dynamical systems.
With the aim of fostering a new generation of scientists who have been trained in both mathematical/computational skills and neuroscientific methodologies, the Bernstein Center Berlin has set up two international, interdisciplinary graduate programs.
The Master program offers fifteen places per year and is delivered in partnership by the three Berlin universities as well as the Charité Medical School.
The final degree, Master of Science (M.Sc.), is jointly awarded by the Humboldt University and the Berlin University of Technology. The two-year program is fully taught in English and applicants with different backgrounds coming from the fields of computer science, cognitive sciences, mathematics, natural sciences, and engineering are accepted. The candidates should provide evidence for above-average mathematical skills as well as a strong interest in the neurosciences.
The curriculum is subdivided into ten modules, whose contents include theoretical neuroscience, advanced programming, data acquisition and computational analysis, machine learning and modeling of experimental data, with a strong focus on a complementary theoretical and experimental training. Each module is composed of different components thus integrating a theoretical lecture with practical lab experience and programming tutorials. Three lab rotations and a master thesis are accomplished in the second year. The aim of the program is to grant the students an interdisciplinary education and an early contact to the neurocomputational research environment. Graduates can extend their acquired abilities in the BCCN's Doctoral program for which scholarships are available each year.
The Doctoral Program is mainly conducted within the framework of the Research Training Group "Sensory Computation in Neural Systems" (GRK 1589/2) based at the Technische Universität Berlin and funded by the German Research Council. This training group gathers some of the current BCCN project leaders as well as further research groups and around 40 students including fellows and associates. Each student is jointly supervised by at least two principal investigators or associated junior researchers with complementary expertise and supported by a training program worth 25 ECTS credit points, which includes scientific courses and the teaching of transferable skills. The students attend an advanced lecture series held by the project leaders and autonomously organize regular events such as an informal PhD Meeting, a Training Group Colloquium with outstanding invited speakers and a Journal Club. Training in presentation and writing skills, grant writing, time and conflict management are offered by the program as well as through the infrastructure of the Berlin Universities.
Accepted fellows are granted a scholarship of approx. 1500 €/month and are financially supported by the program for visiting conferences and purchasing consumables and equipment for the thesis research. Doctoral students funded by other sources can apply for association to the training group provided that their research thematically fits the scope of the GRK.Graduate
All students who are interested in neuroscience and have a strong mathematical background are welcome to apply. In accordance with the interdisciplinary nature of Computational Neuroscience, the program encourages students from diverse disciplines such as natural sciences, engineering, or mathematics to file their application.
Deadline: March 15th
Recommended (not mandatory):
The application should include the following:
Students may apply before receiving their Bachelor's degree. Applicants who cannot provide proof of a first degree until the application deadline will be preliminarily admitted. This preliminary admission will be subject to the condition subsequent that the applicant will prove the successful completion of the first degree until the start of lectures.
Important note: All copies have to be certified according to the Technische Universität Berlin guidelines. All documents that are not in German, English have to be translated by an officially approved translator.
Where to apply
All students have to apply through uni-assist (including German applicants!). No application fee is to be paid for submitting your application.
Phone: +49 30 666 44 345
For any question regarding the formalities of the application please contact the Servicebereich Master of Technische Universität Berlin.
For questions concerning the required qualification contact the teaching coordinator of the Master Program: firstname.lastname@example.org
Research Training Group "Sensory Computation in Neural Systems" (GRK 1589/2)
Deadline: March 15th
Candidates admitted to the PhD program are expected to hold a Master's degree (or equivalent) in a relevant subject (e.g., neuroscience, cognitive science, computer science, physics, ...) and have the required advanced mathematical background.
How to apply:
For more details see: www.computational-neuroscience-berlin.de
Humboldt-Universität zu Berlin
Philippstr. 13, Haus 6
Prof. Michael Brecht
Margret Franke: email@example.com
Coordination Graduate Programs
Robert Martin: firstname.lastname@example.org
Phone: +49 (0)30 2093-6773
Prof. Klaus Obermayer
MAR 5-6, NI, Informatik
Technische Universität Berlin
D-10587 Berlin, Germany
Teaching coordination and applications
Robert Martin: email@example.com
Pictures: Marcel Stimberg, Vinzenz Schönfelder, Arno Onken, Daniela Pelz