Publisher
source

Richard Gao

11 months ago

PhD Positions in Computational Neural Dynamics, Machine Learning, and AI for Neuroscience Goethe University Frankfurt in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

The position is funded for 3 years at 75% E13 TV-G-U (German public sector salary scale). No explicit stipend amount is mentioned. The funding covers salary; no details on tuition coverage are provided.

Deadline

Expired

Country flag

Country

Germany

University

Goethe University Frankfurt

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Keywords

Computer Science
Machine Learning
Cognitive Science
Signal Processing
Artificial Intelligence
Computational Neuroscience
Cognitive
Brain Dynamics
Statistics
- Neuroscience
Brain Circuits
Statistical Data Analysis

About this position

Goethe University Frankfurt is offering two fully funded PhD positions in Computational Neural Dynamics, Machine Learning, and AI for Neuroscience. The positions are part of Prof. Richard Gao's new research group at the Institute of Computer Science, Center for Cognition and Computation. The group focuses on the intersection of computational neuroscience and artificial intelligence, studying circuit mechanisms and functional roles of brain dynamics using computational methods such as machine learning, simulator models, signal processing, and statistical data analysis. The research aims to bridge neurobiology and cognition with AI, leveraging insights from the brain to inform artificial intelligence.

Successful candidates will join a vibrant academic environment in Frankfurt, collaborating with multiple universities and Max Planck Institutes, and participating in the ICNF Network. The group values diversity and encourages applications from candidates of all backgrounds. The working language is English, and German proficiency is not required.

Applicants should have a master's degree or equivalent research experience in computational neuroscience, computer science (ML/AI), bio/electrical/computer engineering, or a related field. Strong programming skills in Python and relevant libraries are essential. Required experience includes at least one of the following: computational modeling of neural circuits, training artificial neural networks in PyTorch or other deep learning frameworks, or signal processing and statistical data analysis. Experience in multiple areas is preferred. Interest in neurobiology, brain circuits, and cognition is expected, along with a desire for independent research and a positive group environment.

The positions are funded for three years at 75% E13 TV-G-U. The application deadline is December 31, 2025, or until filled, with a flexible start date expected in February 2026. To apply, candidates should send a combined PDF including a statement of interest, CV, transcripts, GitHub/project link, and contact information for two referees to Prof. Richard Gao at [email protected]. For more details, visit the group website.

Funding details

The position is funded for 3 years at 75% E13 TV-G-U (German public sector salary scale). No explicit stipend amount is mentioned. The funding covers salary; no details on tuition coverage are provided.

What's required

Applicants must hold a master's degree or equivalent research experience in computational neuroscience, computer science (ML/AI), bio/electrical/computer engineering, or a related field. Strong quantitative and scientific programming skills in Python and relevant libraries are required. Prior experience in at least one of the following is mandatory: computational modeling of neural circuits, training artificial neural networks in PyTorch or other deep learning frameworks, or signal processing and statistical data analysis. Experience in multiple areas is preferred. Interest in neurobiology, brain circuits, and cognition is expected. Candidates should have strong written and spoken English; German proficiency is not required. A desire for independent research and a positive group environment is valued.

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Professors

Professor

University Name
Country flag

Germany

Research Interests

Computational Neuroscience

Artificial Intelligence

Computer Science

Signal Processing

- Neuroscience