About the job
FL119 is seeking a (Senior) Scientist, Computational Neuroscience to join our team. Leveling is flexible based on experience. This role will focus on building scalable computational pipelines for biophysical modeling and applying machine learning techniques to large-scale neural datasets.
Responsibilities
Own the development of end-to-end computational pipelines for biophysical modeling of neurons and neural populations.
Implement machine learning and statistical inference methods to construct and analyze bio-realistic networks from neural recordings.
Actively shape the technical roadmap by proposing, prototyping, and evaluating modeling and inference approaches in close collaboration with the broader team.
Qualifications
Minimum
MSc or PhD in Computational Neuroscience, Physics, Applied Mathematics, Computer Science, AI/ML, or a related field.
2+ years of full-time industry or postdoctoral experience (5+ years for MSc).
Strong experience with computational modeling of neural systems.
Hands-on experience applying machine learning or statistical methods to complex time-series data.
Proficiency in Python and scientific computing libraries (e.g., NumPy, SciPy, Pandas), and familiarity with ML frameworks such as PyTorch or TensorFlow.
Comfort working in high-ambiguity R&D environments and building novel methods from first principles.
Preferred
Passion for working at the intersection of AI and experimental biology.