Neural Data Scientist — Neuro‑AI & Brain Analytics

Max Planck Institute of Colloids and Interfaces; Florida; On-site; USD 120,000 - 150,000; Full time

Job summary

Max Planck Florida Institute for Neuroscience (MPFI) seeks a Neural Data Scientist to advance a Neuro-AI initiative, embedding computational neuroscience within a world-class experimental community. You will apply AI/ML to develop scalable analytical tools and predictive models that accelerate discovery and open science across labs.

The role emphasizes translating hypotheses into testable analyses, building accessible pipelines, and mentoring researchers while leveraging HPC/cloud resources for

Qualifications

• PhD in Machine Learning, Computer Science, Biomedical Engineering, Computational Neuroscience, Biophysics, or related field.
• Demonstrated expertise in AI/ML (especially deep learning) applied to biological or neural data.
• Track record of collaboration with experimentalists influencing design or hypotheses.

Responsibilities

• Translate open biological questions into precise hypotheses about neural dynamics and behavior.
• Develop AI-driven analysis and predictive modeling for neural data across modalities.
• Create GUI-based analysis pipelines enabling collaboration between experimentalists and modelers.
• Oversee HPC/cloud resources for large-scale modeling and reproducible workflows.
• Mentor experimentalists and foster theory-experiment collaboration.

Skills

AI/ML expertise

Python programming

Collaboration

Education

PhD in ML/CS/biomedical field

Tools

PyTorch

TensorFlow

JAX

Job description

Max Planck Florida Institute for Neuroscience (MPFI) seeks a Neural Data Scientist to advance a Neuro-AI initiative, embedding computational neuroscience within a world-class experimental community. You will apply AI/ML to develop scalable analytical tools and predictive models that accelerate discovery and open science across labs.

The role emphasizes translating hypotheses into testable analyses, building accessible pipelines, and mentoring researchers while leveraging HPC/cloud resources for