(Senior) Scientist, Computational Signal Processing at Flagship Pioneering, Inc.

Cambridge, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Feb, 26

Salary

209000.0

Posted On

20 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Signal Processing, Machine Learning, Data Pipelines, Python, C/C++, Scientific Computing, Algorithm Design, Statistical Learning, Neuroimaging, Electrophysiology, Data Analysis, Prototyping, AI, Experimental Biology

Industry

Biotechnology Research

Description

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 neuroimaging technologies to decipher the neural code and 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 creative and talented Senior Computational Scientist, Signal Processing to join our team. Leveling is flexible based on experience. This role will focus on building data pipelines by applying signal processing and machine learning methods to large datasets generated by our neuroimaging platform. The role is based in Cambridge, Massachusetts, with a preference for on-site engagement. International candidates are welcome to apply. How You Will Contribute: Spearhead the design and development of signal processing pipeline for high frequency (kHz), noisy, spatiotemporal signal data. Implementation of ML techniques for extracting quantitative parameters and functional relationships from signals to uncover transferable representations of cognition. Deployment of tools and scripts for managing and analyzing large experimental datasets. Shape the technical roadmap and lead the design of pivotal experiments. Must-have Qualifications: MSc or PhD in Computational Neuroscience, Computer Science, AI/ML, or a related field. 2+ years of full-time industry or postdoctoral experience (5+ years for MSc). Experience developing signal processing and machine learning algorithms for time-series data (electrophysiological, neuro, audio, sequencing, etc.), statistical learning, and algorithm design. Proficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas, PyTorch or Tensorflow), and C/C++ for algorithm development and data analysis. Comfort in high-ambiguity R&D environments and experience prototyping algorithms from scratch. Passion for working at the intersection of AI and experimental biology. Preferred Experience: Previous experience with processing and analyzing electrophysiology data. Contributed to open-source data projects in biology/chemistry. ABOUT FLAGSHIP PIONEERING Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies 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 at www.flagshippioneering.com. At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact. We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship. 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. #LI-MB1 The salary range for this role is $115,000 - $209,000. 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.

Responsibilities

The role involves designing and developing signal processing pipelines for high-frequency, noisy, spatiotemporal signal data. Additionally, the candidate will implement machine learning techniques to extract quantitative parameters and manage large experimental datasets.