AI-Guided Sustainable Soft Polymers and Laser Induced Graphene Transfer for Soft Robotics New Grad

PhD AI-Guided Sustainable Soft Polymers and Laser Induced Graphene Transfer for Soft Robotics and E-Textiles

About Tyndall
Tyndall National Institute is an international leader in semiconductors, photonics and deep-tech research and innovation. As a leading collaborative European research institute, Tyndall is a key actor and hosting partner in the delivery of the ‘Chips for Europe Initiative’ (EU Chips Act).

Tyndall is Ireland’s leading research and innovation organisation and it is the national focal point for excellence in deep-tech research, development and graduate training at the convergence of nanotechnology, microelectronics, photonics, electronics and AI. Tyndall is recognised as an international research leader in semiconductor, chip and digital technologies, particularly as applied to the fields of Information & Communications, Health & Life Sciences, Agritech & Food Security, Energy and Climate Mitigation, emerging fields such as quantum, and novel computing paradigms.

The Institute’s key objective is to see frontier research activities having a significant impact on economic development and societal challenges in Ireland, Europe and beyond. Central to Tyndall’s mission is delivering economic impact through research excellence in partnership with industry and academia. With an annual turnover of more than €50m, the Institute has a community of over 600 researchers, engineers, support staff, postgraduate students, interns and industry researchers-in-residence.

With significant committed Irish government support, Tyndall will grow to be 1,000 people by 2030, with approximately 750 researchers, including 250 PhD students. A new 17,000 m2 research building is under development adjacent to the Cork headquarters and there are developing plans to expand Tyndall’s existing Dublin research labs and to establish other research sites within Ireland.

Tyndall’s expansion is also supported by recent national and EU funding wins for significant (M€10’s) additional research equipment across a range of areas such as semiconductor processing, microscopy, quantum technologies, heterogeneous integration, ultra-high speed optical communications and RF through THz characterisation.

About the Team
Within the Micro & Nano Systems (MNS) Centre at Tyndall, one of our core strengths is development and integration of advanced materials, devices and systems for smart sensing, wearable technologies and sustainable electronics. The Integrated Nanomaterials (InMAT) team conducts research on sustainable functional materials, biodegradable and bio-derived polymers, direct laser writing, laser-induced graphene, wearable sensors, energy devices and circular electronic-textile systems.

About the Role
As part of the Research Ireland (RI) funded Rinn AI centre of excellence, the InMAT team is offering a fully funded PhD studentship focused on the use of artificial intelligence (AI) to accelerate the design of environmentally responsible soft polymers and the development of Laser-Induced Graphene (LIG) transfer processes for circular electronic textiles and soft robotic systems. The project will investigate the transfer of LIG from donor substrates onto soft polymer surfaces using low-temperature, pressure-assisted, adhesive-assisted or reversible transfer approaches. Particular emphasis will be placed on preserving the porous structure and electrical conductivity of LIG while achieving strong, durable and, where appropriate, reversible adhesion to the polymer substrate. AI will be used to predict material and process performance, identify the most influential variables and propose new polymer formulations and transfer conditions.

Key Duties & Responsibilities
As the successful candidate, you will:

• Design, prepare and characterise environmentally responsible soft polymer formulations based on bio-derived, biodegradable, recyclable or low-hazard materials.
• Develop and optimise the fabrication and transfer of porous Laser-Induced Graphene structures onto soft, flexible and stretchable polymer substrates.
• Investigate how polymer formulation, surface properties and transfer conditions influence mechanical behaviour, adhesion, pattern fidelity, electrical conductivity, durability and end-of-life performance.
• Characterise the resulting materials and interfaces using mechanical, electrical, electrochemical, spectroscopic and imaging techniques, including tensile and cyclic testing, adhesion measurements, sheet-resistance analysis and microscopy.
• Develop structured datasets and apply machine learning and multi-objective optimisation to predict performance and guide the selection of new formulations and transfer conditions.
• Integrate optimised materials into proof-of-concept e-textile or soft-robotic components, collaborate with researchers across Tyndall, UCC and the Rinn AI Centre, and contribute to publications, dissemination, education and public-engagement activities while complying with relevant quality, safety and regulatory requirements.
• Participate in training, professional development opportunities, Education and Public Engagement activities, as required;
• Ensure compliance with Tyndall’s Quality Management Systems, Health and Safety standards, and other regulations;
• To carry out any additional duties and provide support which may reasonably be required within the general scope and level of the post.

Essential Criteria

• An honours undergraduate degree, or equivalent, in Materials Science, Polymer Science, Chemistry, Chemical Engineering, Mechanical Engineering, Biomedical Engineering, Physics, Computational Materials Science or a closely related discipline.
• Demonstrated research or project experience in polymers, soft materials, hydrogels, elastomers, composites, biomaterials or related functional materials.
• Experience in laboratory-based materials preparation, processing, characterisation or device fabrication.
• Evidence of quantitative data-analysis skills and a strong interest in developing and applying artificial intelligence or machine-learning methods to experimental materials research.
• Ability to undertake interdisciplinary experimental and computational research, work both independently and collaboratively, and communicate research effectively in written and verbal support form.

Desirable Criteria

• Programming experience in Python, R, MATLAB or a related language.
• Experience with machine learning, statistical modelling, design of experiments, Gaussian processes, Bayesian optimisation, active learning or multi-objective optimisation.
• Experience with polymer mechanical characterisation, tensile testing, rheology, dynamic mechanical analysis, cyclic testing or viscoelastic modelling.
• Experience in Laser-Induced Graphene, direct laser writing, laser processing, material transfer, printing or flexible-electronics fabrication.
• Experience in soft robotics, wearable electronics, electronic textiles, flexible sensors or stretchable devices.

Candidate profile
The ideal candidate will be motivated by research at the interface of materials science and artificial intelligence. They will be comfortable working both in the laboratory and with computational tools and will have a strong interest in sustainable materials, data-driven discovery and interdisciplinary research.
The candidate should be methodical, curious and willing to work with small, heterogeneous and sometimes noisy experimental datasets. A commitment to careful documentation, reproducible research and the recording of both successful and unsuccessful experiments will be essential.

Advanced expertise in artificial intelligence is not required at the outset. Appropriate training and co-supervision will be provided. However, applicants should demonstrate strong quantitative ability and a genuine motivation to develop machine-learning and data-science skills during the PhD.

What We Offer

• A generous tax-free scholarship stipend payment including tuition fees covered.
• A full-time, fixed-term PhD studentship for four years.
• 20 days per annum annual leave for full-time research students, in addition to public holidays.
• Full coverage of travel expenses to international conferences to present project outcomes.
• Training and development opportunities are also provided.
• Mardyke Sports Arena -Students – free when registered with UCC
• Free Park and Ride Service
• Also see here for more information

Terms of Studentship
Contract: Full Time
Contract Type: Fixed Term
Duration: 4 Years

The annual stipend is €25,00.00. In addition, annual tuition fees will be paid by the Tyndall National Institute.
Contract: Full Time/Fixed Term

Informal enquiries can be made in confidence to Dr Daniela Iacopino

The closing date for applications for this position is 1pm, 20th November 2026
Expected start date: October/November 2026

Application Instructions
Applicants should submit:

• an up-to-date CV or résumé;
• a brief motivation letter outlining their interest in the project and explaining how they meet the essential criteria;
• academic transcripts;
• contact details for at least two academic or professional referees.

The motivation letter should describe any relevant experience in materials science, polymers, experimental research, programming, data analysis, machine learning, sustainability, robotics or electronic textiles.

Postgraduate applicants whose first language is not English must provide evidence of English-language proficiency in accordance with University College Cork regulations. Certificates should normally be valid and issued within the period specified by UCC.(https://www.ucc.ie/en/study/comparison/english/postgraduate/). Certificates should be valid (usually less than 2 years old) and should be uploaded with their application.

Please note that Garda vetting and/or an international police-clearance check may form part of the selection process.

The University may, at its discretion, make additional appointments from this competition following the conclusion of the selection process. Appointment will be subject to University approval and the terms of the employment control framework for the higher-education sector. Tyndall National Institute does not require the assistance of recruitment agencies.

Tyndall National Institute at University College Cork is an Equal Opportunities Employer.