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Hydrofunctionalizations of alkenes and alkynes—among the most important examples of which are hydrocyanation and hydroformylation—are processes of tremendous industrial importance, enabling the synthesis of pharmaceuticals, polymers, and functional materials. One of the fundamental limitations of these reactions is the lack of precise control over selectivity. This leads to the formation of product mixtures, including regio- and stereoisomers as well as isomerization products, which is particularly significant for unsymmetrical substrates. These issues arise mainly from the limitations of established catalysts based on transition-metal complexes (Ni, Rh) supported by symmetrically constructed phosphine ligands, which do not provide adequate selectivity control. This project aims to develop a new, holistic approach to controlling selectivity in hydrocyanation and hydroformylation, based on the use of desymmetrized phosphine ligands and advanced artificial intelligence methods. The planned strategy relies on the synthesis of a broad library of new catalysts (>100) with diverse structures and the evaluation of their catalytic performance in both processes (>1000 substrate–catalyst–conditions combinations). The resulting experimental dataset on catalyst activity (TON, TOF) and selectivity will be used to develop predictive machine-learning models that enable accurate in silico identification of optimal catalyst–substrate–conditions combinations and the design of new, more selective catalysts. This will substantially reduce the time required to develop catalysts with the desired selectivity and will lower experimental costs in future practical applications. The proposed approach has the potential to significantly improve industrial processes, leading to more sustainable and economically efficient technologies for the production of high value-added compounds.

• Participation in the preparation of new ligands/catalysts
• Comprehensive structural characterization of the obtained compounds
• Optimization of the synthesis of selected compounds

- a scholarship position in the Institute of Physical Chemistry PAS with a monthly stipend of 2500 PLN  financed from FIRST TEAM FENG No. FENG.02.02-IP.05-0063/25 project, which is financed from the funds of Priority 2 of the European Funds for a Smart Economy 2021–2027 Program (FENG) Action 2.2 First Team, with the Intermediate Institution being the Foundation for Polish Science.

The stipend is planned for 12 months.  

- the opportunity to work in an interdisciplinary, international research team

- engagement into an ambitious research program and possibility to build the academic career

The selected candidate will join a highly experienced, multidisciplinary team working at the interface of catalysis, organic synthesis, and data-driven chemistry. They will have the opportunity to develop advanced experimental expertise in ligand/catalyst library synthesis for hydrofunctionalizations reactions. The project will enable them to address selectivity challenges of direct industrial relevance and contribute to more sustainable, economically efficient catalytic technologies.

At the starting date of the work within the project, the candidate should be a student of first or second degree studies or uniform master's studies.

Student status in chemistry (or related) field is required, as well as a strong interest in chemical synthesis and catalysis. The candidate is expected to be highly motivated for scientific work, capable of independent problem solving, able to work effectively in a team, and systematic and reliable in conducting experiments. Prior experience in organic synthesis or coordination chemistry, and understanding scientific literature will be considered an advantage.

The committee will consider the following criteria:

• Competence to carry out specific tasks in the research project
• Previous scientific achievements
• Fluency in English