• CFD, Mixing, and Transport o Apply CFD or reduced-order mixing models to evaluate vessel geometry, impeller selection, mixing times, local shear, and heat/mass transfer impacts on crystallization outcomes. o Integrate CFD insights with PBM to anticipate scale-up effects on supersaturation distribution, PSD, and impurity incorporation. • Crystallization Science & Mechanistic Studies o Design and execute data-rich experiments on primary/secondary nucleation, growth, agglomeration, and breakage. o Use in situ PAT (e.g., FBRM, PVM, Raman, mid-FTIR/ReactIR, ATR-UV/Vis, calorimetry) and offline analytics (e.g., XRPD, DSC, TGA, SEM, laser diffraction, dynamic image analysis) to monitor supersaturation, solid form, and PSD evolution. • Kinetics, PBM & Thermodynamics o Estimate kinetic parameters for nucleation, growth, agglomeration, and breakage; build and validate PBMs to predict PSD and shape under varying supersaturation and hydrodynamics. o Apply thermodynamic and phase-equilibrium models (e.g., solubility modeling, activity coefficient methods, metastable zone width) to inform supersaturation and seeding strategies. • Process Design, Optimization, and Scale-up o Develop first-principles models to guide seeding policies, cooling or antisolvent addition profiles, and batch vs. continuous mode selection. o Define robust operating envelopes and support tech transfer to pilot and commercial assets. • PAT Strategy & Control o Lead PAT strategy for crystallization: sensor selection, probe placement, calibration, data integrity, and maintenance. o Develop soft sensors and multivariate models; integrate PAT with control strategies for real-time monitoring of supersaturation, nucleation events, and PSD proxies. o Collaborate with automation/controls to deploy feedback/feedforward control leveraging PAT data. • Model-Based Experimentation o Design targeted experiments to reduce model uncertainty and refine kinetic/thermodynamic mechanisms, minimizing empirical iteration. • Route, Form, and Downstream Integration o Partner with solid-state and analytical teams on polymorph landscapes, salt/cocrystal options, and isolation/washing/drying impacts on quality and PSD. • Digital & Data Science Integration o Integrate PBM/CFD and thermodynamic models into digital workflows and data historians; collaborate on AI/ML approaches for soft sensing, parameter estimation, and optimization. • Cross-functional Collaboration & Documentation o Translate model and PAT insights into process decisions and control strategies; author technical reports and contribute to regulatory documentation related to crystallization and particle attributes. • Fluent English speaking and writing capability

• Returnee PhD/ or experienced returnee Master • Major in Chemical Engineering or closely related field with relevant industrial experience in crystallization, particle engineering, or process modeling (computational fluid dynamics 计算流体力学) • Hands-on experience implementing PAT for crystallization (e.g., FBRM, PVM, Raman, FTIR), including probe selection, chemometric model development, calibration/validation, and data quality assurance. • Demonstrated expertise in crystallization kinetics, PBM, and phase equilibrium/thermodynamics, with a track record of translating models into process designs (seeding strategies, cooling/antisolvent profiles, continuous crystallization). • Proficiency with modeling tools such as gPROMS, Aspen Plus/Custom Modeler, Dynochem, MATLAB, Python, or equivalent for PBM, parameter estimation, and uncertainty analysis. • Practical understanding of mixing, heat/mass transfer, and their influence on nucleation/growth; experience with CFD or mixing analyses applied to crystallization. • Ability to design and execute lab and pilot studies to generate high-quality data for model development and validation.