Scientist / Senior Scientist, Machine Learning

Seismic Tx • Watertown, MA

84d

About The Position

Seismic Therapeutic, a cutting-edge biomedicines company at the intersection of machine learning, protein engineering, and immunology, is seeking a creative, independently-minded machine learning scientist to help accelerate the Impact Platform for the computational discovery and optimization of new biologic drugs. Seismic's machine learning platform enables on-demand generation and optimization of protein therapeutics to fight diseases of the immune system, using the power of artificial intelligence to translate audacious ideas into breakthrough drugs. We are dedicated to building a supportive culture around a superstar team, while keeping the unmet needs of patients at the center of our goals. Seismic has the tools, skills, ideas and people to make this vision a reality. Working closely with our team of machine learning scientists, structural biologists, immunologists and others, you will develop and apply innovative machine learning approaches to optimize natural proteins for clinical applications and design novel classes of synthetic proteins with therapeutic functions.

Requirements

• PhD in Mathematics, Computational Biology, Computer Science, Statistics or a related field. Exceptional candidates with extensive computational experience and a PhD in a non-computational field will also be considered.
• 3+ years of industry experience with developing and applying machine learning methods to create new biological drugs, using deep learning models such as variational autoencoders and graph neural networks.
• Application of ML in the field of drug discovery is essential with hands-on experience in the following: protein engineering, or statistical genetics are especially relevant.
• Demonstrated experience collaborating with wet lab scientists to generate and analyze real-world data in an applied setting, especially in the context of pharmaceutical development.
• Proficiency in Python and data analysis with Numpy/Scipy, R, or another statistical programming language.
• A strong drive to collaborate and communicate with a diverse and vibrant team of both dry and wet lab scientists.

Nice To Haves

• Experience with AWS, Google Cloud, or another cloud computing framework.
• Familiarity with Dash, R Shiny, or another interactive app development framework.
• Application of ML in the fields of genomics and immunology.
• Publications in major scientific journals that apply machine learning methods to problems in molecular or structural biology.

Responsibilities

• Design and train new classes of machine learning models to optimize natural proteins for therapeutic properties and design synthetic proteins with novel therapeutic functions.
• Spearhead computational de novo antibody design efforts to create new therapeutics targeting challenging antigens.
• Integrate diverse external and internal data sources including protein sequence, structure, function, and molecular characterization data to enable detailed modulation and multi-objective optimization of protein properties.
• Work with a diverse team of protein scientists, immunologists, and clinical experts to tailor modeling efforts toward high-impact therapeutic applications.
• Establish robust data infrastructure to enable machine learning model training and deployment of data analysis and visualization tools.
• Develop production-quality code in a team setting for use by both computational and wet-lab scientists.
• Present progress from scientific work in regular meetings and prepare reports and slide decks for broader internal and external communication.

What This Job Offers

• Career Level: Mid Level
• Industry: Publishing Industries
• Education Level: Ph.D. or professional degree
• Number of Employees: 51-100 employees