Senior Scientist I/II, Chemistry & Formulations

COMPANY DESCRIPTION

Our start-up is building a novel chemical discovery platform to reshape how we develop formulations at the molecular level. By combining artificial intelligence with a cutting-edge laboratory discovery pipeline, our interdisciplinary team will chart an unexplored chemical landscape, enabling breakthroughs in drug delivery, agrichemical formulation, and safe, high-performance industrial chemicals.

Our company is backed by Flagship Pioneering, a biotechnology origination company that has founded and developed over 115 scientific ventures over the past 25 years. Flagship Pioneering is dedicated to the development of an ecosystem of first-in-category life sciences companies, resulting in $20+ billion in aggregate value, 500+ issued patents, and more than 50 clinical trials for novel therapeutic agents.

THE ROLE

We are seeking an experienced formulations chemist to lead the design, strategy, and implementation of a high-throughput chemical formulation and testing pipeline. This position will focus on building a rapid and evolving system for manufacturing chemical mixtures and measuring the physiochemical properties of these mixtures at various temperatures and levels of hydration. This position will also coordinate heavily with a Machine Learning Lead to integrate the bench top pipeline output with the training and output of a predictive model for formulation chemistry. The ideal candidate will have a strong background in organic chemistry, high-throughput chemical screening, spectroscopy, calorimetry, and other advanced techniques for the physical characterization of chemicals. 

KEY RESPONSIBILITIES

• Manufacturing formulations
  • Design and implement a scalable high-throughput workflow for generating diverse chemical mixtures.
  • Rigorously catalog known formulations for comparison to newly developed and untested formulations.
  • Establish automated liquid handling, dosing, and mixing protocols to ensure reproducibility and throughput.
  • Develop standard operating procedures (SOPs) for safe handling, storage, and disposal of raw materials and formulations.
  • Collaborate with upstream ML lead on formulation design workflows that maximize our canvassing of chemical property space and support the generation of high-quality, broad-coverage training data.
• Characterizing formulation properties
  • Assess viscosity, solubility, and other physiochemical features under different hydration and temperature conditions.
  • Apply spectroscopy (UV-Vis, IR, fluorescence) to quantify molecular interactions and stability.
  • Use calorimetry and thermal gravimetric analysis to measure thermodynamic and thermal stability profiles of formulations.
  • Develop and validate assays to track long-term stability and degradation of formulations.
• Screening formulation-cargo interactions
  • Design assays to evaluate compatibility of formulations with diverse small molecules, peptides, proteins, and nucleic acids.
  • Measure cargo protection and stability (e.g., aggregation, precipitation, degradation) under varied conditions.
  • Integrate biophysical characterization methods (DLS, CD, IR, LCMS) to assess cargo–formulation interactions.

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• Ph.D. in Organic Chemistry, Physical Chemistry, Chemical Engineering, Materials Science, or a related field + 5 years of experience (including 2 years of industry at minimum).
• Extensive hands-on experience with formulation chemistry, high-throughput chemical screening, or analytical method development.
• Demonstrated expertise in chemical characterization techniques such as spectroscopy (UV-Vis, IR, NMR, fluorescence), calorimetry (DSC, ITC), and rheology.
• Proven ability to characterize physicochemical properties of complex mixtures under varying environmental conditions.
• Strong background in designing and executing high-throughput or automated experimental workflows.
• Committed team player with the ability to communicate and work collaboratively with ML scientists, lab scientists and operational team members.
• Prior leadership or team management experience preferred.
• Experience integrating benchtop experimental data into machine learning pipelines or predictive modeling workflows preferred.
• Strong understanding of thermodynamics, kinetics, and intermolecular interactions in multicomponent systems preferred.
• Familiarity with high-throughput robotics, automation platforms, or liquid handling systems for screening of solvents and liquids preferred.
• Knowledge of data analysis pipelines, including scripting skills (e.g., Python, R, MATLAB) for handling large experimental datasets preferred.
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