Germany : 6 PhD fellowships at Bernstein Center for Computational Neuroscience, Berlin

The Bernstein Center for Computational Neuroscience (BCCN) Berlin invites applications for fellowships of its new graduate school “Sensory Computations in Neural Systems” (GRK 1589/1).

The scientific program of the research training group “Sensory Computation in Neural Systems” is focused on sensory coding and perception.

The research topics will falls into two broad categories, (1) theoretical aspects, with the aim to develop computational methods for the study of sensory computations, with a focus on time and dynamics, and (2) applying this theory to experiments. Every PhD project will be collaborative in nature and is supervised by at least two investigators with complementary expertise. Theory projects usually combine one investigator with a machine learning/engineering background with one investigator with experience in neural or cognitive modeling – in order to assure theoretical expertise and biological relevance. Experiment-theory projects are conducted by at least one investigator with a strong experimental and one investigator with a strong theoretical background.

The program thus aims to combine the four key aspects:

• a focus on functional hypotheses about perception (“computation” rather than “dynamics”),
• a focus on behavioral paradigms, linking perception with cognitive functions,
• a focus on advanced machine learning techniques not yet widely used for the analysis and modeling of neural systems, and
• a focus on interdisciplinary training implemented by strict co-supervision through researchers with complementary expertise, and complemented by a structured teaching program.

See below for a list of example topics that would fit the scope of the graduate program.

Scientific Environment

The graduate school is based in Berlin, a vibrant city in Central Europe, boasting a broad range of high-profile initiatives in the area of Neuroscience and Machine Learning, including the Bernstein Center for Computational Neuroscience, The Berlin School of Mind and Brain, Bernstein Foci on Neurotechnology and on Learning, the Neurocure excellence cluster, and many others.

See below for a list of the principle investigators directly involved in this graduate program.

Sample topics

Below you will find 19 example research projects which fall into the current research agenda of the principal investigators and which are also fully within the scope of this research training group.

A. Temporal Aspects and Dynamical Systems.

A.1 Classification of Single-Trial EEG in Non-Stationary Environments

A.2 Information Flow and Time Reversal

A.3 Approximation Techniques for Information Transfer in Stochastically Driven Neurons

A.4 A Continuous Time Analysis of Neural Encoding

A.5 Correlated Spike Trains: A Non-renewal Approach

A.6 Computational Models of Goal-Directed Behavior

A.7 Cortical Information Processing under Non-stationary Network State Conditions

B. Understanding Local Sensory Computation: Invasive Studies

B.1 The Neural Code of Visual Short-term Memory

B.2 The Computational Role of Cortical Feedback

B.3 Decoding Biologically Relevant Stimuli from Cortical Population

B.4 Signal Processing in Noise: Functional Specialization in a Size-Constrained Nervous System

B.5 Cooperativity of Cortical Ensembles during Natural Vision

C. Understanding Global Sensory Computation: Non-invasive Studies

C.1 Critical Feature Identification in Psychophysics

C.2 Computational Neuroimaging of Saliency Signals in the Human Visual System

C.3 Reward-related Perceptual Learning

C.4 The Role of Impulsivity in Reward-regulated Human Decision Making

C.5 Neural and Computational Mechanisms of Reward Rate Optimization in Human Decision Making

C.6 Modeling the Spatiotemporal Neuronal Dynamics of Conscious Tactile Information Processing

C.7 Task-dependent Sensorimotor Integration and Behavior Recognition

Requirements

Application

Candidates admitted to the PhD program are expected to hold a Masters degree (or equivalent) in a relevant subject (e.g., neuroscience, cognitive science, computer science, physics, …) and have the required advanced mathematical background.

Applicants should submit the following documents:

1. curriculum vitae (including a list of publications, if applicable);
2. letter of motivation;
3. copies of certificates and transcripts of records;
4. proof of proficiency in English;
5. brief description of the completed master or diploma thesis and brief outlook on the future PhD project;
6. two letters of reference;
7. names of potential supervisors (NB: candidates are strongly encouraged to contact potential supervisors and discuss potential projects with them before the application deadline).

The deadline for application is March 15, 2010.

Selection:

Successful applicants will be invited for a short presentation and an interview, expected to take place in the second half of April 2010. The applicants should prepare a 15 min presentation of their master or diploma thesis including a description of their motivation for the future PhD project.

Selection criteria include:

• competence and research experience in CNS/machine learning;
• proficiency in English;
• mathematical background;
• scientific and educational track record;
• research interests and motivation.
  

Contact

For further details, required material, principle investigators and example topics of the graduate school, please refer to http://www.bccn-berlin.de or contact Robert Martin rm@cs.tu-berlin.de.

Further Information

Application Deadline : 15 March 2010

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Posted on 2010-01-18 11:20:57

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