Flagship Pioneering
FL85 | Cambridge, MA Senior Scientist, Machine Learning
Flagship Pioneering, Cambridge, Massachusetts, us, 02140
FL85 is a Flagship backed, privately held biotechnology company on a mission to transform the current approach to information molecule therapeutics to unlock their full therapeutic potential. In recent years, we have begun to experience the power of information molecules in treating historically undruggable diseases and in designing therapies with unprecedented turnaround times. FL85’s platform integrates nanoparticle development with world-class informatics technologies and a novel pipeline of experimentation and discovery to drive a new generation of highly effective, therapeutically relevant information molecule therapies. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!Position SummaryWe believe we are at the cusp of a nucleic acid medicine revolution powered by programmable medicines and machine learning. We are leveraging machine learning and fast iterative cycles with a world-class wet lab team to guide and improve the design of the next generation of delivery vehicles for nucleic acid therapeutics. These delivery vehicles are complex self-assembled particles at the intersection of chemistry, biology and self assembly, and ML can be leveraged to help generate and predict across all design aspects.To this end, we are seeking a rigorous, self-motivated, creative
Senior Machine Learning Scientist . As one of the first computational scientists and engineers on the team, you will have the chance to greatly impact the organization and drive projects end-to-end, from ideation, to proof of concept, to production-level data pipelines. You will be expected to develop innovative methods for molecular generation and optimization, large self-supervised pre-training, and active learning strategies to close the loop with the wet lab. The successful candidate will work closely with experimental scientists to rapidly advance various scientific programs, be comfortable iterating rapidly in development phase, while building robust and reliable pipelines in production. This individual will join a world-class, dynamic, and highly collaborative team that is driving a novel platform technology.Responsibilities:Understanding the latest developments in ML architecturesTraining and customizing ML modelsRigorously evaluating ML modelsInvestigating datasets and developing intuition around statistical relationships, biases, and outliersFollowing and triaging ML literature and rapidly prototyping new ideasMaking connections and understanding one or more scientific fields beyond CS/ML and coming up with novel cross-disciplinary ideasEffectively communicating results to stakeholders with various levels of ML expertiseYou will have the opportunity to develop:A strong domain expertise in nucleic acid medicines and nucleic acid medicine deliveryA deep relationship with a world class lab teamAutomated, production level data pipelinesA deep expertise in ML for chemistry applicationsTooling and analytics for wet lab teamQualifications:Ph.D. in a computer science, statistics, or a related field with demonstrated experience applying computational methods to scientific applications2-5 years developing ML methods to solve scientific problems, with a particular interest towards applications to molecular generation, active learning, Bayesian optimization and/or experimental design as well as adjacent fields such as biology, chemistry, immunology, or genomicsProficiency in Python and machine learning frameworksEnergetic self-starter with the ability to work effectively in an entrepreneurial environmentExcellent analytical skills and ability to synthesize & communicate complex information rapidly and effectivelyUnmatched sense of urgencyA deep passion for using novel machine learning techniques to unlock new impact potential across healthNice to have:Deep expertise in managing Linux environments using Docker, as well as package management using conda, pip, apt/yum or other package management toolsExperience deploying robust, automated workflows using workflow management tools and compute cluster infrastructuresPublications in major ML conferences or scientific journals that apply ML to problems in the sciences, including but not limited to molecular biology, chemistry, physics, structural biology, genetics, or other key questions that center around molecular prediction, design, and/or generationDemonstrated experience developing software in a team settingLocation:
Cambridge, MAAbout FlagshipFlagship Pioneering is a biotechnology 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 Pioneering and our ecosystem companies are
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.
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Senior Machine Learning Scientist . As one of the first computational scientists and engineers on the team, you will have the chance to greatly impact the organization and drive projects end-to-end, from ideation, to proof of concept, to production-level data pipelines. You will be expected to develop innovative methods for molecular generation and optimization, large self-supervised pre-training, and active learning strategies to close the loop with the wet lab. The successful candidate will work closely with experimental scientists to rapidly advance various scientific programs, be comfortable iterating rapidly in development phase, while building robust and reliable pipelines in production. This individual will join a world-class, dynamic, and highly collaborative team that is driving a novel platform technology.Responsibilities:Understanding the latest developments in ML architecturesTraining and customizing ML modelsRigorously evaluating ML modelsInvestigating datasets and developing intuition around statistical relationships, biases, and outliersFollowing and triaging ML literature and rapidly prototyping new ideasMaking connections and understanding one or more scientific fields beyond CS/ML and coming up with novel cross-disciplinary ideasEffectively communicating results to stakeholders with various levels of ML expertiseYou will have the opportunity to develop:A strong domain expertise in nucleic acid medicines and nucleic acid medicine deliveryA deep relationship with a world class lab teamAutomated, production level data pipelinesA deep expertise in ML for chemistry applicationsTooling and analytics for wet lab teamQualifications:Ph.D. in a computer science, statistics, or a related field with demonstrated experience applying computational methods to scientific applications2-5 years developing ML methods to solve scientific problems, with a particular interest towards applications to molecular generation, active learning, Bayesian optimization and/or experimental design as well as adjacent fields such as biology, chemistry, immunology, or genomicsProficiency in Python and machine learning frameworksEnergetic self-starter with the ability to work effectively in an entrepreneurial environmentExcellent analytical skills and ability to synthesize & communicate complex information rapidly and effectivelyUnmatched sense of urgencyA deep passion for using novel machine learning techniques to unlock new impact potential across healthNice to have:Deep expertise in managing Linux environments using Docker, as well as package management using conda, pip, apt/yum or other package management toolsExperience deploying robust, automated workflows using workflow management tools and compute cluster infrastructuresPublications in major ML conferences or scientific journals that apply ML to problems in the sciences, including but not limited to molecular biology, chemistry, physics, structural biology, genetics, or other key questions that center around molecular prediction, design, and/or generationDemonstrated experience developing software in a team settingLocation:
Cambridge, MAAbout FlagshipFlagship Pioneering is a biotechnology 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 Pioneering and our ecosystem companies are
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.
#J-18808-Ljbffr