Praktika und Abschlussarbeiten

Praktika

Computational Systems Neuroscience

The department of Computational Systems Neuroscience welcomes undergrad students from the fields of Biology, Neuroscience, Computer Science, Physics, or Engineering to participate in their research. They are offering projects in computational and experimental neuroscience, including modeling studies, studies in animal behavior and in neurophysiology.

Required skills: depending on project

Ort

Universität Köln

Kontakt

Abteilungsleitung
Martin Nawrot
mnawrot@uni-koeln.de

Visual and olfactory systems

The Department of Sensory and Sensorimotor Systems is open for students for internships and theses in their labs.

Research foci are visual and olfactory functions in the human and animal brain and their elicited behavioral responses, and other related topics in brain science. Research methods include visual psychophysics, zebrafish behavior and neuroscience, computational modeling, data analysis, human event related potential measurements, fMRI and eye tracking.

Eligibility: depending on requirements of individual training program

Required skills: depending on project

Ort

Max-Planck-Institut für biologische Kybernetik Tübingen

Kontakt

Abteilungsleitung
Li Zhaoping
zhaoping.li.admin@tuebingen.mpg.de

Cognitive and neural mechanisms underlying learning and memory

The computational neuroscience group researches on the cognitive and neural mechanisms underlying learning and memory using computational methods. Topics for Bachelor/Master theses are available and the lab is open for collaborations, offering expertise on episodic memory, spatial navigation, hippocampus, neural networks, and reinforcement learning. The main language of communication is English.

Skills to be learned: reinforcement learning, neural networks, parallel computing

Required skills: programming

Ort

Ruhr-Universität Bochum

Kontakt

Gruppenleiter
Sen Cheng
sen.cheng@rub.de

High performance computing (HPC)

The Simulation and Data Lab Neuroscience offers students an insight into the world of High-Performance Computing (HPC) and how HPC can be efficiently used for neuroscience research, from modelling and simulation to data analysis and neuroimaging. Visiting students should have some programming skills, e.g. in C, C++ or Python, to be able to use their visit for a (first) project with HPC and/or data resources.

Skills to be learned: high-performance computing, data analysis, visualisation technology for neuroscience

Required skills: programming

Ort

Jülich Supercomputing Centre (JSC)

Kontakt

Wiss. Koordination
Maren Frings
slns@fz-juelich.de

Abschlussarbeiten

Directional information in hippocampal place cells populations

Hippocampal place cells not only decode the current position but also the running direction of an animal. The interconnectedness between those codes is less explored but of fundamental importance for the understanding of hippocampal function in navigation and memory processes. This project will apply and refine analysis tools for extracellularly recorded spiking data obtained during free foraging. Students will be exposed to classic methods and literature on hippocampal in-vivo physiology and state-of-the art machine learning methods.

Eligibility: Student must be enrolled at University of Freiburg

Required skills: Experience in Python and statistical methods

Background: Neurobiology

Ort

Bernstein Center Freiburg, Universität Freiburg

Kontakt

Bernstein Koordinationsstelle
Janina Radny
j.radny@fz-juelich.de

Modeling in neurophysiology and optogenetics

Depending on background and interest: Modeling single neurons and neuronal networks in the thalamocortical system (simple and biophysical models); analysis of single neuron and network encoding of sensory/behavioral stimuli and interactions between neurons (data from large-scale silicon probe in vivo experiments with targeted optogenetic interventions); information theoretic analysis of neural data; identification of neuronal ensembles.

Student background: physics, applied mathematics, computer science, data science

Required skills: depending on project: linear algebra, differential equations, data visualization, Python

Ort

Universität Heidelberg, Institut für Physiologie und Pathophysiologie

Kontakt

Bernstein Koordinationsstelle
Janina Radny
j.radny@fz-juelich.de