Machine Learning Scientist - Data Team

Do you have a passion for science and take pride in excellent work? Can you master cutting-edge technologies and rapidly develop new experimental methods? Are you highly collaborative, hardworking and creative?

Who we are

Dyno Therapeutics is a Cambridge based, VC-backed biotech startup that uses next-gen DNA technologies and machine learning to engineer Adeno-associated Virus (AAV) capsids for effective delivery of gene therapies.

What we offer you

As a member of our new and quickly growing company, you’ll help us shape Dyno from the very beginning into a startup that not only takes its scientific mission seriously but also provides a positive and supportive workplace environment. And Dyno will have the opportunity to benefit from the insight, diversity, and talent that you’ll bring. Together, we’ll help turn gene therapy into reality.

Our mission

Dyno wants to help transform the gene therapy universe. AAV capsids are the vector of choice when it comes to delivering transgenes in vivofor gene therapy and genome editing. Eclipsing all of its predecessors, AAV is at the forefront of gene delivery approaches both at the research level and at the clinical front. Dyno aims to make it even better. Doing so will enable treatment for millions of patients with currently incurable, often disabling and deadly diseases, and we invite you to become a part of that.

How?

Dyno has a transformative pipeline for AAV engineering that harnesses DNA library synthesis, high-throughput sequencing, and machine learning to improve AAV capsids and lift them above current fitness landscape boundaries into unexplored areas. While AAV is the current go-to method for gene delivery, there’s much room for improvement with regard to central factors like delivery efficiency, tissue and cell-type targeting, evading the immune system, and others. These limitations stand between the many significant advances achieved in gene therapy research and their translation into real-world, effective therapies. Our approach resolves these issues, generating next-gen AAV vectors that move gene therapies from the lab into clinics for the benefit of patients worldwide.

Where?

Dyno is located near Kendall Square in Cambridge within the dynamic LabCentral community, alongside other new companies that are turning ideas into reality, changing the biotech and medical scenes. We’ve recently joined this exciting hub and are thrilled to expand our Team with hardworking, highly qualified, highly motivated individuals.

General role: The data science team is at the heart of Dyno’s platform, and your work as a part of this team will have a potentially major impact on the future of gene therapy. The team's responsibilities span biological data analysis, machine learning model building, computational optimization, and experimental design of high-throughput viral libraries. Opportunities to apply rigorous theoretical approaches from combinatorial optimization, bayesian optimization, bandit strategies, reinforcement learning, natural language processing, and compressive sensing in our platform abound. The successful candidate will have expertise in one of these (or related) topics and would like to apply them to a new domain. The field of capsid engineering is ripe with problems that are interesting from a learning perspective, and Dyno is well-placed to generate data at a scale at which these approaches can be fruitful.

As an early member of our team, you will have the opportunity to help craft our approach, shape our culture, and positively impact people’s lives. You will work closely with a group of talented, driven, and fun scientists. We are located in Lab Central in a dynamic community of biotech startups. The guideline below should give you a rough picture of who we are looking for, but depending on your background, you may bring different qualities to our team. Don't hesitate to write to us if you think you are a good fit. We offer competitive benefits.

Qualifications:

  • BS, MS, or Ph.D. in a quantitative field (Machine learning, Math, Physics, CS, Operations Research, Statistics, ...) or equivalent experience.
  • Strong theoretical foundation in machine learning or a related domain.
  • Expertise in one or more general-purpose programming languages (such as Python or C/C++.)
  • Passion for creative problem solving.
  • Proven experience with at least one machine learning library (such as Tensorflow or pyTorch).

Nice to have:

  • Papers in machine learning or EECS conferences (NIPS, ICLR, ICML, INFORMS, FOCS,...)
  • AI Internships or residencies at leading AI companies.
  • 1 or more years experience working in a data science team in a machine-learning driven company.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Job Types: Full-time, Internship

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