PhD Position for Deep Learning for Optogenetic Sensory Restoration

How to apply

Who to contact?	ekfz@sinzlab.org
Email subject	Start with "[ML PhD]"
What to include?	All applications What degree do you (soon) hold (e.g. "Master in Applied Data Science")? Curriculum Vitae Statement of motivation (max 500 words) outlining your personal interest in this research area. Your latest transcript of records A short list of which relevant skills you have and which you would like to acquire. Links to code you have written (e.g. github or bitbucket) If applicable, at most two publications or pre-print you (co)-authored Known programming languages and experience Names and emails of two references. Possible start date If you apply with your own project idea Do you bring funding or not? A concise (pdf, max 1/2 page) “research proposal” on a project you would be interested working on. This is not binding but helps to get the conversation started.

PhD Position (3 years) in Deep Learning for Optogenetic Sensory Restoration

The Else Kröner Fresenius Center for Optogenetic Therapies (EKFZ OT) at the Universitätsmedizin Göttingen (UMG) and the University of Göttingen is seeking a talented PhD student with expertise in computer science/machine learning to join our interdisciplinary team. This position is funded by EKFZ OT and will be jointly supervised by Prof. Marcus Jeschke, Prof. Emilie Macé, and Prof. Fabian Sinz.

Project Description

This PhD project aims to develop deep learning-based strategies to determine optimal optogenetic stimulation patterns for maximizing information transfer to the cortex in sensory restoration applications. The project will leverage a closed-loop modeling approach to optimize both optogenetic cochlear implants and vision restoration technologies.

The successful candidate will:

1. Analyze electrophysiological data in response to optogenetic stimuli in sensory-deprived animals
2. Build deep neural network models to predict neuronal population responses to optogenetic stimulation
3. Use these models to compute stimulation patterns that maximize information transfer
4. Verify and refine the models through experimental testing in collaboration with experimentalists

This is the first attempt to optimize stimulation patterns directly from cortical activity, with potential applications in future clinical trials for vision restoration and optical cochlear implants.

Your Profile

Required Qualifications

• Master’s degree in Computer Science, Machine Learning, Computational Neuroscience, or a related field
• Strong programming skills, particularly in Python and deep learning frameworks (PyTorch, TensorFlow, or similar)
• Experience with neural networks and deep learning models
• Solid understanding of mathematics and statistics
• Excellent analytical and problem-solving skills
• Good communication skills and ability to work in an interdisciplinary team

Preferred Qualifications

• Background in computational neuroscience or neural data analysis
• Experience with time series data and signal processing
• Knowledge of convolutional neural networks and representation learning
• Familiarity with neurophysiological data
• Interest in sensory systems and optogenetics

What We Offer

• A 3-year, full-time position (100% E13 TV-L)
• The opportunity to work at the intersection of machine learning, neuroscience, and optogenetics
• Access to cutting-edge experimental facilities and data
• Close collaboration with leading researchers in auditory neuroscience, vision science, and machine learning
• Integration into the vibrant neuroscience and data science community at the University of Göttingen
• The chance to contribute to groundbreaking research with potential clinical applications

The Environment

You will be jointly mentored by three laboratories:

• Prof. Dr. Marcus Jeschke (Cognitive Hearing in Primates lab, German Primate Center) - expert in optogenetic cochlear implants and auditory cortex recordings
• Prof. Dr. Emilie Macé (Dynamics of Excitable Cell Networks, University Medical Center Göttingen) - expert in optogenetic vision restoration and visual cortex recordings
• Prof. Dr. Fabian Sinz (Machine Learning, University of Göttingen) - expert in NeuroAI

The position is based in Göttingen, Germany, a vibrant university city with a rich scientific tradition and home to numerous research institutions.

Expected start date: 1.10.2025 or as early as possible.