Richard Gao
2 months ago
PhD Positions in Computational Neural Dynamics, Machine Learning, and AI for Neuroscience at Goethe University Frankfurt Goethe University Frankfurt in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
The positions are funded for 3 years at 75% E13 TV-G-U (m/f/d), which is a standard German PhD salary scale. No information on tuition coverage or stipend amount is provided.
Deadline
Expired
Country
Germany
University
Goethe University Frankfurt

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Where to contact
Official Email
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About this position
Prof. Richard Gao is recruiting two PhD students for his new research group at Goethe University Frankfurt, within 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 aim is to bridge neurobiology and cognition while advancing AI4Neuro, leveraging insights from brain science to inform AI.
As founding members, PhD students will help shape the team culture and receive training in academic research, scientific literacy, and computational methods in neuroscience and machine learning. The group is part of a vibrant community with collaborative opportunities at multiple universities and Max Planck Institutes, and is affiliated with the ICNF Network. Located in Frankfurt, the group benefits from a diverse international academic environment, with English as the working language.
Applicants should hold a master's degree or equivalent research experience in computational neuroscience, computer science (ML/AI), bio/electrical/computer engineering, or a related field. Required skills include strong quantitative and scientific programming abilities in Python and relevant libraries, and prior experience in at least one of the following: computational modeling of neural circuits, training artificial neural networks in Python or other deep learning frameworks, or signal processing and statistical data analysis. Interest in neurobiology, brain circuits, and cognition is expected, along with a desire for independent research and strong English communication skills. German proficiency is not required.
The positions are funded for three years at 75% E13 TV-G-U (m/f/d), a standard German PhD salary scale. The application deadline is December 31, 2025, or until filled, with an expected start date of February 2026 (flexible). To apply, candidates should send a single combined PDF including a statement of interest, CV, transcripts, GitHub or project repository link, and contact information for two references to [email protected]. For more details, visit the group website.
Funding details
The positions are funded for 3 years at 75% E13 TV-G-U (m/f/d), which is a standard German PhD salary scale. No information on tuition coverage or stipend amount is provided.
What's required
Applicants must 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 quantitative and scientific programming skills in Python and relevant libraries are required. Prior experience in at least one of the following is necessary: computational modeling of neural circuits, training artificial neural networks in Python 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 demonstrate a desire for independent research and contribute positively to the group environment. Strong written and spoken English is required; German proficiency is not necessary.
How to apply
Send a single combined PDF to [email protected] with the subject line 'PhD Application | Firstname Lastname'. Include a statement of interest (1 page max), CV, transcripts, GitHub or project repository link, and contact information for two potential references. Visit the group website for more details.
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