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.

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.

• 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.

• 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…