Research Associate for AI-Enabled Process Optimization and Resource Recovery

Join the cutting-edge R3VOLUTION and Cardimed projects, two game-changing projects aiming to enable over 90% water reuse in water-intensive industries, recover more than 45% of effluent solutes, reuse over 50% of waste heat, and eliminate 100% of hazardous substances. As the Integration Lead for an AI-based Digital Process Assistant (DPA), you will spearhead the deployment of a real-time digital twin at multiple pilot sites in the petrochemical, bio-based chemical, pulp and paper, and steel industries. Collaborating closely with diverse project partners, you will ensure that the DPA seamlessly connects to live sensor data, runs simulations to fine-tune process variables, and provides intelligent recommendations to optimize water usage, resource recovery, and system performance.

You will define and implement robust data retrieval, storage, and processing frameworks that ensure compatibility with existing monitoring and control systems. You will feed real-time sensor data into the digital assistant to facilitate simulations and generate process recommendations. You will conduct offline simulations to validate and calibrate Machine Learning models using experimental data from physical demonstration sites. You will support iterative testing and re-training of these models in operational environments by monitoring performance against key indicators. You will oversee the live operation of the digital assistant, refining its parameters to meet project targets. Finally, you will collaborate with membrane technology experts, process engineers, and data scientists to continuously improve the solution and share findings through technical reports and publications.