Computer Science Neuroscience Jobs in Massachusetts

Cambridge, MA USA

The Company

Flagship Labs 119 Inc. (FL119) is an early-stage technology company pioneering a new frontier at the intersection of neuroscience and computation. We are developing next-generation technologies to transform how intelligent systems are built. We believe that the future of artificial intelligence demands a fundamental rethinking of today’s paradigms. Our mission is bold and urgent: to build a future where naturalistic, robust intelligence can emerge and operate sustainably at scale.

FL119 is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. At FL119, we are uniquely cross-functional and collaborative. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

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.

How You Will Contribute:

• 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.

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.

About Flagship Pioneering

Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship atwww.flagshippioneering.com .

Flagship Pioneering is committed toequal employment opportunityregardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

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. FL119 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL119's good faith estimate as of the date of publication and may be modified in the future.

Privacy Notice for Applicants:When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of your personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.