Job offer

The proposed solution and innovation, driven by the Mecat network, centers on establishing the integrated European framework where the development of mechanocatalysis is a cohesive, closed-loop process. The central innovation is the mechanocatalysis, which proactively embeds sustainability by ensuring that metrics are design parameters rather than retrospective evaluations. This is achieved through the direct integration of real-time data from operando-instrumented mechanochemical platforms (such as ball mills and extruders, delivering multimodal datasets like Raman and FTIR) into predictive kinetic and reactor models. These models subsequently inform validated Integrated Life Cycle Assessment (LCA) and Techno-Economic Analysis (TEA) workflows, which guide the design of catalysts and process optimisation. The crucial move toward industrial relevance, and a core strength of Mecat, is the guaranteed ability to achieve pilot-scale implementation, secured by the direct availability of necessary advanced reactors within the consortium. Mecat’s unique structure is not limited to lab-bench scale; its industrial partners and research pillars provide collective access to specialized, high-throughput equipment, including twin-screw extruders, Resonant Acoustic Mixing (RAM) systems, and industrial mills. This collective infrastructure allows the seamless translation of powder-scale discoveries to continuous processing and validation at the kilogram scale. By unifying this methodology from lab to pilot scale through five interconnected pillars- mechanistic elucidation, catalyst design, pilot-scale implementation, quantitative sustainability benchmarking, and interdisciplinary doctoral training- Mecat establishes the foundations for reproducible, industry-ready, solvent-free catalysis and polymer upcycling/recycling, directly addressing the current immaturity of the field. Together, these pillars create an integrated innovation pipeline that aligns directly with MSCA DN objectives: high-quality, interdisciplinary training; intersectoral mobility; and the development of researchers equipped to drive Europe’s green transition., This doctoral project will develop robust methods to measure and understand mechanocatalytic reactions in ball mills, resonant acoustic mixers (RAM) and extruders using real-time experimental variables. The DC will design experimental workflows that quantify mechanical input (e.g. frequency, load, energy) and link it to conversion, yield and product quality in representative polymer recycling and catalytic model reactions. Building on BAM’s expertise in advanced materials characterisation and data analysis, analytical, modelling and data-science approaches will be combined to interpret in situ and operando datasets from the Mecat consortium and its partners. The resulting quantitative protocols will deliver high-precision evaluation of mechanochemical processes and generate process-control recommendations and upscaling strategies that feed directly into other Mecat DC projects and industrial collaborators., Doctoral candidates will spend time two secondments during their 36 month employment contracts. Anticipated secondments for this position are:

1. Syensqo, Lyon, France: industrial mechanocatalysis / scale-up: 3-month secondment focused on scale-up strategies and industrial instrument integration for mechanocatalytic processes.
2. University of Birmingham, UK: 3-month secondment to study and evaluate mechanocatalytic model reactions, and to benchmark the DC’s real-time analysis tools on well-defined mechanochemical systems.

Specific Requirements

Process

Interested candidates should submit a single PDF document to: franziska.emmerling@bam.de, named with your full name and the position: “DC7_Mecat_Lastname_Firstname”.

Master Degree or equivalent, We are looking for a highly motivated candidate with:

• A Master’s degree (or equivalent) in chemistry, materials science, chemical engineering or a closely related discipline.
• Strong background in solid-state chemistry, catalysis or advanced materials characterisation.
• Experience with at least one of the following is an advantage: X-ray diffraction, Raman / IR spectroscopy, operando or in situ methods, process analytics, or data-driven analysis of experimental results.
• Very good command of English (written and spoken); knowledge of German is an asset but not mandatory.
• Enthusiasm for working in an international, interdisciplinary environment and for spending, 1. A detailed CV (maximum two pages), specifying educational background (name of university/universities, year degree(s) obtained, title(s) of degree(s)), qualifications, work experience, skills, research interests, list of publications (if any) and the names and contact details of two referees. 2. A motivation letter (maximum two pages), describing the candidate’s interest in the network, previous research experience, and current research interest outlining the fit to the desired PhD Project. If you are planning to apply to more than one position in the network, please limit your applications to three positions maximum (from DC1 to DC15) and please provide a separate document detailing which positions you have applied for. 3. Copy of passport or National Identify Card. 4. Copies of academic certificates (BSc, MSc, and any other relevant diplomas), translated into English, including expected final grade and date. 5. Proof of English proficiency, demonstrated by IELTS, TOEFL, or a university certification confirming that the degree or MSc thesis was conducted in English. 6. Two recommendation letters (maximum 1 page each).

Only documents in English will be accepted.

Applications failing to include the requested documentation, who do not indicate the preferred projects or do not meet the eligibility criteria, will not be considered.

Languages ENGLISH, * MSc degree. Candidates must hold a Master’s degree (or equivalent) in chemistry, chemical engineering or related fields. Candidates must not have been awarded a previous PhD degree.

• English proficiency: Applicants must have excellent English proficiency, at least B2 level (written and spoken).

• Cutting-edge research training mechanochemistry as a green and alternative synthesis methods..
• First-hand experience in mechanochemistry and mechanocatalysis, work at synchrotron and advanced analytical facilities, in situ / operando analysis (XRD, Raman), and data-driven reaction engineering.
• International, interdisciplinary, and intersectoral mobility, with secondments across Europe.
• Joint supervision by leading experts from academia and industry.
• Participation in international conferences, workshops, and transferable skills training.
• Competitive salary, mobility allowance following MSCA-DN funding rules.

An attractive salary in accordance with the Marie Skłodowska-Curie Action regulations for doctoral candiates is offered. Eligibility criteria

Mecat brings together nine leading academic institutions and 12 non-academic partners, forming a uniquely comprehensive consortium that covers the entire mechanocatalysis value chain. This alignment is not found in any current MSCA DN or Horizon Europe project.

• Academic leaders (UP, UNICA, BAM, RUB, UoB, UU) provide expertise in mechanochemistry, catalysis, polymer chemistry and operando methods, while ENS Lyon and HUB will deliver the doctorate diploma only.
• Applied research organisations (IFPEN, FCBA, Fraunhofer) bridge fundamental discoveries with process engineering and industrial validation.
• Technology providers (Retsch, Microtrac, WAB, HTE Gmbh) supply advanced mechanochemical reactors, mill instrumentation and high-throughput platforms.
• Industrial end-users (Saint-Gobain, Syensqo, Johnson Matthey, ARD) define real-world constraints, host secondments and provide pilot-scale environments.
• Sustainability experts (UBx, WeLOOP) ensure that LCA and TEA steer decision-making throughout the project.

This consortium ensures complete coverage of all required competencies, from laboratory-scale mechanistic insight to industrial demonstration and provides DCs with a vibrant intersectoral training environment. The continuous exchange of materials, data, and models among partners embeds each DC in a real, functioning innovation chain, rather than isolated research tasks.