Project Synopsis
The recent advent of powerful Generative AI, particularly Large Language Models (LLMs), is poised to transform the entire industrial innovation process. The CampAIgn project, funded by the EU's Interreg VI-A Slovenia-Austria program, is positioned at the forefront of this paradigm shift. Our mission is to develop and establish a new methodology for research and development where generative AI acts as a collaborative partner in the innovation process for both materials and products. The project brings together a consortium of four institutions—the Faculty of Polymer Technology (SI), the University of Ljubljana (SI), Carinthia University of Applied Sciences (AT), and Materials Center Leoben (AT)—to create a rich, interdisciplinary environment dedicated to pioneering this work. This research position will focus specifically on tackling these challenges within a real-world polymer innovation case study. Traditional material discovery and development is an inherently complex endeavour, characterised by vast formulation spaces, intricate process-structure-property relationships, and lengthy, resource-intensive cycles of iterative experimentation. The CampAIgn project aims to address this by positioning generative AI as a collaborative partner to accelerate discovery, enhance creativity, and optimise complex polymer systems. This is not merely about applying existing software; it is about exploring a new frontier of scientific inquiry by investigating how human researchers and intelligent systems can work in synergy.
Position Overview and Research Focus
As a key researcher in this workstream, your role will be to explore the boundaries of AI's application in polymer science. This is an opportunity to move beyond conventional R&D and address fundamental research questions at the leading edge of both materials and computer science:
- Knowledge Synthesis and Hypothesis Generation: How can Large Language Models (LLMs) be systematically prompted to synthesise decades of disparate scientific literature to propose novel material formulations or processing strategies that a human researcher might overlook?
- Navigating Complexity: How can generative models be combined with predictive AI (hybrid AI) to more efficiently navigate complex, multi-dimensional parameter spaces for material and process optimization, reducing the need for costly and time-consuming physical experiments?
- Human-AI Collaboration: What are the most effective human-AI collaborative workflows in a material science laboratory setting? How can AI be used to overcome creative blocks, identify non-obvious correlations in data, and guide experimental design?
Your research will be anchored in a real-world industrial case study, providing a robust framework for testing hypotheses and validating your findings. This case study will serve a dual purpose: solving a tangible challenge for an industry partner while acting as a living laboratory for your research into human-AI interaction in an R&D setting. You will be responsible for designing the experimental approach, deploying various AI tools, and analysing the results to build a systematic, evidence-based understanding of AI's potential. The intellectual contributions from this work are expected to be substantial, leading to high-impact publications and forming the core of a doctoral dissertation.
The Structured Doctoral Research Pathway
Recognizing the academic potential of this research, the position is explicitly designed to support the candidate's pursuit of a doctoral degree.
- Primary Role: Your principal role is a full-time, salaried Researcher at the Faculty of Polymer Technology.
- External PhD Enrollment: We are fully committed to supporting your academic ambitions. FTPO will provide active, formal support to facilitate your enrollment in a PhD program at a separate, accredited university or research institute.
- Research Alignment and Mentorship: The research you conduct as an employee of FTPO is designed to be of a scope, depth, and originality that will directly constitute the core of your doctoral dissertation. You will receive dedicated mentorship from senior academic staff at FTPO to guide this research, and we will leverage our academic network to help you connect with potential external academic supervisors. This structure allows you to earn a professional salary and gain valuable project experience while concurrently fulfilling the requirements for a PhD.
Key Responsibilities
- Lead Polymer Innovation Case Study: Assume primary responsibility for the planning, execution, and analysis of the project's polymer materials innovation case study, conducted in close collaboration with an industrial SME partner.
- Technical Development and AI Application: Apply advanced AI tools, with a focus on Generative AI, for tasks including literature research, experimental planning, material property modelling, process optimisation and data analysis.
- Methodology and Content Creation: Document research findings and contribute directly to the development of the project's general AI-Driven Industrial Innovation Methodology and the creation of technical content for training programs.
- Contribute to AI Tool Screening: Provide essential technical expertise to the project's continuous screening and evaluation of emerging AI models and tools.
- Stakeholder Engagement and Dissemination: Actively participate in stakeholder workshops and meetings; prepare research findings for dissemination through project reports, peer-reviewed publications, and presentations at international scientific conferences.
Candidate Profile
Essential Qualifications:
- A Master’s degree (or equivalent) in Polymer Science/Engineering, Materials Science, Chemical Engineering, Mechanical Engineering or a closely related discipline, completed by the contract start date.
- A solid theoretical foundation in the principles of polymer materials or processing technologies.
- A demonstrable, sophisticated interest in the application of AI tools to solve complex scientific or technical problems.
- Excellent analytical, critical thinking, and problem-solving skills.
- The ability to work with a high degree of independence and intellectual ownership.
- Full professional fluency in written and spoken English.
Desirable Attributes:
- Experience in a research environment, including literature reviews, experimental design, synthesis/processing, characterisation, data analysis, scientific communication (writing of scientific papers).
- While not a prerequisite, familiarity with programming concepts (e.g., Python) or experience with data analysis tools is advantageous.
- Strong communication skills and the ability to work effectively within a collaborative, international team.
What We Offer
- A 36-month, full-time employment contract as a Researcher.
- A competitive salary and benefits package commensurate with qualifications and experience.
- A structured pathway and formal institutional support for pursuing a PhD at an external university.
- A dedicated budget for travel (conferences, workshops, and project partner meetings), materials and AI licences.
- Immersion in an international, English-speaking research consortium with strong industry connections across Central Europe.
- Comprehensive support with the relocation process for international candidates. The position is based in Slovenj Gradec, Slovenia, a country renowned for its safety, natural beauty, and high quality of life.
Application Process
Interested candidates are invited to submit their application as a single PDF file to [email protected] no later than 14th November 2025. The application must include:
- A detailed Curriculum Vitae, including a list of any publications or relevant projects.
- A Letter of Motivation (max. 2 pages) outlining your suitability for the research position, your perspective on the role of AI in material science, and your specific interest in the doctoral pathway.
- Complete academic transcripts for all Bachelor's and Master's level studies.
- The names and contact information for at least one academic or professional reference.
Job Information at a Glance
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Organisation/Company
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Faculty of Polymer Technology (FTPO)
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Research Field
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Engineering > Materials engineering; Chemistry > Polymer chemistry; Computer science > Artificial intelligence
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Researcher Profile
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First Stage Researcher (R1)
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Country
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Slovenia
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Application Deadline
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14 November 2025 - 23:59 (CET)
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Type of Contract
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Temporary (36 months)
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Job Status
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Full-time
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EU Framework Programme
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Interreg VI-A Slovenia-Austria
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Work Location
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Company/Institute
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Faculty of Polymer Technology
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Country
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Slovenia
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City
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Slovenj Gradec
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Street
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Ozare 19
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Postal Code
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2380
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