(Senior) Scientist, Computational Neuroscience

About the role

The Role: 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. The role is based in Cambridge, Massachusetts, with a preference for on-site engagement. International candidates are welcome to apply.

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.

Requirements

• 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.
• Passion for working at the intersection of AI and experimental biology.

Qualifications

The Ideal Candidate Will Have:

• 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.
• Passion for working at the intersection of AI and experimental biology.

Skills

Skills Required:

• Python programming.
• Scientific computing libraries (NumPy, SciPy, Pandas).
• Machine learning frameworks (PyTorch, TensorFlow).
• Biophysical modeling of neurons and neural populations.
• Statistical inference methods for complex time-series data.

Benefits

FL119 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits.

Pay

The salary range for this role is $132,000 - $259,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience.

Schedule

The role is based in Cambridge, Massachusetts, with a preference for on-site engagement. International candidates are welcome to apply.