Scientist, Computational Sensing

Posted 11 Days Ago
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Cambridge, MA, USA
In-Office
115K-165K Annually
Mid level
Biotech
The Role
Develop computational methods to process and interpret nanopore and electrophysiology data. Build event-detection, classification, and fingerprinting pipelines; create quantitative models linking signals to molecular identity; collaborate with experimental teams and ML, protein, and signal-processing groups; establish benchmarking and uncertainty quantification practices.
Summary Generated by Built In
About Tilde (FL110)

Tilde Bio, Inc. (FL110) is building a next-generation biological sensing platform at the intersection of synthetic biology, protein engineering, nanopore biophysics, electrophysiology, signal processing, and machine learning. Our goal is to create programmable biological measurement systems capable of extracting rich molecular information from single-molecule interactions.

We believe nanopores generate a high-dimensional measurement of molecular identity and behavior that remains largely untapped. Unlocking that information requires new computational approaches — ones that don't yet exist — built by people who are comfortable working at the edge of what's known. At Tilde, you will work alongside scientists and engineers from diverse disciplines to help define how a new generation of biological sensing systems extract meaning from the physical world.

Tilde is backed by Flagship Pioneering, which brings the long-term vision and resources needed to build platforms that don't fit neatly into existing categories.

Position Overview

We are looking for a Bioinformatics Scientist to join our Computational Team to help build the analytical foundation that connects nanopore measurements to biological understanding. This role sits at the intersection of biology, physics, signal processing, and machine learning — you will work directly with experimental scientists and engineers to develop methods that transform complex biological measurements into actionable scientific insight.
This role requires creating and implementing  standard pipeline, and goes beyond them. Here, you will build fundamental approaches to understanding and processing electronic data into an interpretable format and create methods to transform that data into actionable sequencing outputs. The problems are open-ended, and many of the analytical frameworks don't exist yet. The right person enjoys working with noisy experimental data, building quantitative models from first principles, and collaborating across disciplines.

What You Will Do
  • Analyze nanopore and electrophysiology datasets to identify biologically meaningful signal features.
  • Develop and implement computational workflows for event detection, classification, and molecular fingerprinting.
  • Build quantitative models that connect nanopore measurements to molecular identity, structure, and function.
  • Collaborate with experimental scientists to interpret results and shape the direction of future experiments.
  • Partner with protein science, signal processing, and machine learning teams to improve platform performance and analytical capabilities.
  • Help establish best practices for benchmarking, validation, and uncertainty quantification as the platform scales.
Qualifications

Required

  • Master's degree plus 3+ years of relevant industry experience, or PhD in Computational Biology, Biophysics, Bioengineering, Physics, Applied Mathematics, Computer Science, Electrical Engineering, or a related quantitative discipline.
  • Strong programming skills in Python and scientific computing environments.
  • Experience analyzing complex biological, physical, or time-series datasets — particularly in the presence of noise and experimental variability.
  • Solid background in at least two of: statistics, machine learning, signal processing, or Bayesian modeling.
  • Comfortable working across experimental and computational domains; able to engage meaningfully with wet-lab scientists on data interpretation.
  • Clear scientific communicator — written and verbal.

Preferred

  • Hands-on experience with nanopore technologies, electrophysiology, or single-molecule measurement platforms.
  • Experience applying deep learning or probabilistic modeling to biological or physical datasets.
  • Background in computational biophysics or time-series analysis of high-dimensional biological signals.
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, 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.

Flagship Pioneering is committed to equal employment opportunity regardless 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 $115,000 - $165,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL110 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL110'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 their 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 [email protected]

Skills Required

  • Master's degree plus 3+ years industry experience, or PhD in a quantitative discipline
  • Strong programming skills in Python and scientific computing environments
  • Experience analyzing complex biological, physical, or time-series datasets with noise and experimental variability
  • Solid background in at least two of: statistics, machine learning, signal processing, or Bayesian modeling
  • Able to engage meaningfully with wet-lab scientists on data interpretation
  • Clear scientific communication skills, written and verbal
  • Hands-on experience with nanopore technologies, electrophysiology, or single-molecule measurement platforms
  • Experience applying deep learning or probabilistic modeling to biological or physical datasets
  • Background in computational biophysics or time-series analysis of high-dimensional biological signals

Flagship Pioneering Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Flagship Pioneering and has not been reviewed or approved by Flagship Pioneering.

  • Fair & Transparent Compensation Feedback suggests salary bands are visible for many Boston/Cambridge roles and pay is considered competitive for key scientific and leadership positions. Transparency in postings supports expectations that offers align with local biotech norms.
  • Healthcare Strength Feedback suggests medical, dental, vision, disability, life insurance, HSA options, and mental-health coverage are comprehensive and well-regarded. Multiple items are employer-verified, reinforcing confidence in core health benefits.
  • Parental & Family Support Feedback suggests maternity/paternity leave and family leave are offered at meaningful levels. These programs sit alongside paid holidays, sick days, and PTO to support family needs.

Flagship Pioneering Insights

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The Company
HQ: Cambridge, MA
475 Employees
Year Founded: 2000

What We Do

Flagship Pioneering conceives, creates, resources, and develops first-in-category life sciences companies to transform human health and sustainability. Since its launch in 2000, the firm has applied a unique, hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in over $30 billion in aggregate value. To date, Flagship is backed by >$3 billion of aggregate capital commitments, of which over $1.5 billion has been deployed toward the founding and growth of its pioneering companies alongside >$10 billion of follow-on investments from other institutions. The current Flagship ecosystem includes Denali Therapeutics (NASDAQ: DNLI), Evelo Biosciences (NASDAQ: EVLO), Moderna Therapeutics (NASDAQ: MRNA), Rubius Therapeutics (NASDAQ: RUBY), Seres Therapeutics (NASDAQ: MCRB), and Syros Pharmaceuticals (NASDAQ: SYRS).

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