Postdoc position in AI-guided mechanistic understanding of coupled redox–dissolution pathways in multi-metal systems Full-time

Postdoc Position in AI-Guided Mechanistic Understanding of Coupled Redox–Dissolution Pathways in Multi-Metal Systems

Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Chemistry, Department of Chemistry – Ångström Laboratory

The project focuses on developing a mechanistic understanding of coupled redox–dissolution pathways in multi-metal oxide systems and how these pathways can be inferred from real-time process signals. Using battery-related hydrometallurgical leaching as a model system, the project combines controlled experiments, real-time monitoring, chemical analysis, and data-driven modelling.

The postdoctoral researcher will investigate how pH, reduction potential, temperature, hydrogen peroxide consumption, and other process signals reflect competing reaction pathways and evolving kinetic regimes. The work will combine experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled systems to industrially relevant black masses from battery recycling.

The project involves collaboration with two industrial partners and includes a research stay of up to three months at a collaborating university in Finland.

The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours.

The duties may also include (e.g.):

• Research within hydrometallurgy, redox–dissolution chemistry, battery recycling, and data-driven modelling
• Develop and apply mechanistic and data-driven models to identify reaction regimes and predict dissolution behaviour
• Analyse time-resolved experimental data using statistical and machine-learning approaches, and validate predictive models using independent experiments
• Design and conduct controlled leaching experiments in multi-metal oxide systems
• Perform and analyse time-resolved measurements of pH, reduction potential temperature, hydrogen peroxide consumption, and metal dissolution
• Investigate reaction kinetics, competing reaction pathways, and evolving surface properties using complementary analytical techniques
• Disseminate results through scientific publications and presentations at international conferences
• Collaborate with academic and industrial partners within the project
• Teaching in the first, second and third cycles of studies
• Administration related to the work duties listed above
• Participation in a research stay of up to three months at a collaborating university in Finland

Requirements: PhD degree in Chemistry, Chemical Engineering, Materials Science, Metallurgical Engineering, Chemical Engineering, Process Engineering, Data Science or a related field or a foreign degree equivalent to a PhD degree in Chemistry, Chemical Engineering, Materials Science, Metallurgical Engineering, Chemical Engineering, Process Engineering, Data Science or a related field. The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

The ability to work both independently and collaboratively is of great importance. The application must include a CV, copies of degree certificates and grades. Applications will be assessed according to the following criteria: fulfilment of eligibility requirements, experience in related fields and personal suitability. The working group is small but highly productive with high demands on collaboration skills.

The candidate must have very good oral and written proficiency in English.

Advanced knowledge and/or practical experience in one of the following areas will be beneficial.

• Experience with machine learning or data-driven modelling, particularly for chemical or process systems
• Experience with Python, or similar tools for data analysis and modelling
• Experience with mechanistic or kinetic modelling of chemical processes
• Experience with hydrometallurgical leaching, redox chemistry, electrochemistry, or reaction kinetics
• Experience with real-time process monitoring and time-resolved experimental data
• Experience with multi-component chemical systems, battery materials, or related experimental systems
• Experience with analytical techniques such as ICP-OES/ICP-MS, XRD, SEM-EDS, or related methods

About the employment: The employment is a temporary position of 2 years according to central collective agreement, with possibility of extension for one more year depending on the availability of funds. Scope of employment 100%. Starting date 2026-11-01 or as agreed. Placement: Uppsala