Neural Data Scientist
Job Description
Max Planck Florida Institute for Neuroscience is seeking a Neural Data Scientist to support a funded Neuro-AI initiative focused on AI-driven analysis and predictive modeling.
Responsibilities
- Collaborate with MPFI experimental research groups to convert open biological questions into precise, testable hypotheses about neural dynamics, computation, and behavior
- Support experimental design by applying theory
- Develop deep learning and dynamical modeling frameworks for large-scale, multi-modal neural datasets, including:
- In vivo functional imaging
- High-density electrophysiology
- Behavior measurements
- Optical or biosensor-derived signals
- Build shared computational tools and platforms, including accessible, GUI-based analysis pipelines, enabling experimentalists to engage with modeling results and refine hypotheses together
- Oversee scientific use of central and/or cloud-based HPC resources for computationally intensive modeling, large-scale data analysis, model training, and reproducible scientific workflows for Neuro-AI projects
Requirements
- PhD in Machine Learning, Computer Science, Biomedical Engineering, Computational Neuroscience, Biophysics, or a related quantitative/biological field
- Proven expertise in AI/ML, especially deep learning, applied to biological, neural, or biosensor datasets
- Documented experience collaborating closely with experimentalists, ideally contributing to experimental design or hypothesis refinement (not limited to post-hoc analysis)
- Proficiency in Python and common ML frameworks, including PyTorch, TensorFlow, and JAX
- Strong record of scientific publications and collaborative, cross-disciplinary research
Technologies
- Python
- PyTorch
- TensorFlow
- JAX
Preferred
- 2+ years of postdoctoral or equivalent research experience
- Background in systems neuroscience, neural recording techniques (electrophysiology and functional imaging such as multiphoton and single-photon calcium and/or neurotransmitter imaging), or biosensor technologies
- Experience developing robust, validated scientific software tools, analysis platforms, or data pipelines for multidisciplinary research teams
- Experience deploying reproducible analysis of workflows, machine learning models, or scientific software on HPC clusters and/or cloud-based computing environments
- Familiarity with dynamical systems, control theory, or generative/probabilistic modeling approaches to behavior and neural data
Location: Jupiter, FL (onsite)
Education: PhD