Research Fellow in Digital Chemistry and Engineering

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Overview

We are seeking a Research Fellow in Reaction Automation to join the EPSRC funded programme R4PID: Reconfigurable, Robotic & Responsive Reactors for Processes through Intensified Development—a flagship project aiming to redefine how synthetic routes are designed, optimised, and prepared for pharmaceutical manufacture.

Responsibilities

  • Develop digitally integrated, microvolume, reconfigurable robotic flow reactors capable of autonomously adapting to diverse synthetic reactions.
  • Generate microvolume reaction pulses with individually controlled conditions.
  • Parallelise droplet‑based microreactor environments for massively increased throughput.
  • Integrate advanced inline sensors (IR, MS, NMR, UV–vis) for real‑time data acquisition.
  • Connect to AI‑driven optimisation and process modelling tools.
  • Provide manufacturing‑quality process data using micro‑ and nanomole quantities.
  • Enable autonomous exploration of discrete variables (catalysts, solvents, reagents).
  • Build a continuous data pipeline from screening to optimisation to scale‑up.

Qualifications

Candidates should possess a strong background in reaction engineering, automation, and data analysis, along with the ability to work independently and collaboratively within a multidisciplinary research environment.

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Company: University of Leeds
Apply for the Research Fellow in Digital Chemistry and Engineering
Location: Leeds
Job Description:

Overview

We are seeking a Research Fellow in Reaction Automation to join the EPSRC funded programme R4PID: Reconfigurable, Robotic & Responsive Reactors for Processes through Intensified Development—a flagship project aiming to redefine how synthetic routes are designed, optimised, and prepared for pharmaceutical manufacture.

Responsibilities

  • Develop digitally integrated, microvolume, reconfigurable robotic flow reactors capable of autonomously adapting to diverse synthetic reactions.
  • Generate microvolume reaction pulses with individually controlled conditions.
  • Parallelise droplet‑based microreactor environments for massively increased throughput.
  • Integrate advanced inline sensors (IR, MS, NMR, UV–vis) for real‑time data acquisition.
  • Connect to AI‑driven optimisation and process modelling tools.
  • Provide manufacturing‑quality process data using micro‑ and nanomole quantities.
  • Enable autonomous exploration of discrete variables (catalysts, solvents, reagents).
  • Build a continuous data pipeline from screening to optimisation to scale‑up.

Qualifications

Candidates should possess a strong background in reaction engineering, automation, and data analysis, along with the ability to work independently and collaboratively within a multidisciplinary research environment.

#J-18808-Ljbffr…

Posted: May 17th, 2026