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Commercial Lead – AutoCircuit (0.4FTE)

We are hiring a Commercial Lead to take AutoCircuit from validated research to market-ready product within 18 months.

Join the AutoCircuit project, a deep-tech initiative developing systems that automatically generate digital circuits from high-level specifications. Funded through an Enterprise Ireland Commercialisation Award, the project has a clear goal: translate validated research into a market-ready product and successful spin-out.

This role sits at the centre of that transition. You will work alongside a strong technical team to define the commercial pathway for AutoCircuit, engaging customers, shaping the value proposition, and building the foundations for a scalable business.

The position offers a genuine opportunity to become part of the founding team of a deep-tech company, with the potential to move into a senior leadership role in the resulting spin-out.

You will own the commercial strategy end-to-end: market discovery, customer validation, partnerships, pricing, and spin-out or licensing. This is a senior, execution-focused role working across research, industry, investors, and university stakeholders.

• Verified customer demand
• Pilot commercial engagements
• Credible revenue model
• Spin-out or licensing readiness

You will work directly with the PI, engineering team, Technology Transfer Office, Enterprise Ireland, and industry partners to drive commercial outcomes.

• Define and execute commercial strategy
• Engage customers and validate product–market fit
• Lead partnerships and commercial negotiations
• Develop pricing, revenue, and go-to-market models
• Prepare spin-out or licensing pathway
• Support investor readiness and due diligence

• 8+ years commercial experience
• Strong track record in deep-tech / AI / software / semiconductor commercialisation
• Experience with spinouts, venture-backed innovation, or tech transfer
• Market development, partnerships, and stakeholder engagement experience
• Ability to operate in early-stage, high-uncertainty environments

• EDA / semiconductor experience
• IP strategy and licensing experience
• VC / deep-tech funding exposure
• Strong international network

A successful outcome is the creation of a spin-out, with the opportunity for the Commercial Lead to take a senior role (e.g. CEO or Head of Business).

Informal enquiries: conor.ryan@ul.ie

Apply via the UL recruitment portal. Search for Recruitment Reference #082489.

Applicants must be legally entitled to work in Ireland. Visa/work permit documentation required where applicable.

Research Assistant / Postdoctoral Researcher (Level 1) – Cloud Infrastructure & UX for AI-Driven Electronic Design

Join the AutoCircuit project to help develop a cutting-edge tool that automatically generates digital circuits from high-level specifications. This is an exciting opportunity to work at the intersection of human-guided AI and hardware design, contributing to a novel toolchain that integrates with industry-standard Electronic Design Automation workflows. Based at UL, you'll collaborate with a dynamic, interdisciplinary team funded by an Enterprise Ireland Commercialisation Award with the goal of forming a successful deep-tech company.

This industry and spinout focused project will position you as a core member of the founding team, giving you the opportunity to secure a founder's equity position upon incorporation and significantly de-risking your entrepreneurial journey. The principal founders are all graduates of successful startups.

The successful candidate will lead the development of a cloud-based platform for AutoCircuit, a next-generation system that automatically generates digital circuit designs from high-level specifications. The role involves creating scalable backend systems, APIs, container-based deployment workflows, and UX interfaces that allow interaction with our ML components.

It is expected that this work will achieve the following:

• Design and implement an intuitive UI to enable users to interact with an ML system.
• Design and implement a secure and scalable backend for an existing software tool.

Potential candidates are encouraged to contact Conor Ryan informally to discuss the positions. Please refer to [UX/Cloudscale Postdoc AutoCircuit] in the subject of your e-mail.

• Postdoctoral Researcher
  • A Doctoral Degree (level 10 NFQ) in Computer Science, Software Engineering, Human-Computer Interaction.
  • Strong publication record in ML/AI (minimum three peer-reviewed publications)
• Research Assistant
  • BSc/MSc in Computer Science, Software Engineering, Human-Computer Interaction with 3+ (BSc) or 1+ (MSc) years relevant experience
• Both Positions
  • Strong coding skills in backend software (e.g. Python, C++, Rust, or Go).

• Experience in UX design, user research, interaction design, HCI, or backend systems that support user-facing features.
• Familiarity with API development (e.g. REST)
• Desire to see your work translate into real-world, commercial impact.
• Experience with cloud platforms (AWS, GCP, Azure)
• Familiarity with EDA flows or engineering design systems.
• DevOps experience (CI/CD, deployment automation)
• Exposure to frontend frameworks (e.g. React, Svelte)
• Knowledge of secure data protocols or access management.
• Track record of open-source or collaborative development.
• Experience with containerised environments (e.g. Docker)

Candidates should be highly motivated, proficient in interaction with others (this is a senior position in a group of 20+ researchers), and have an interest in working with real world problems.

For further information, please feel free to contact Conor Ryan by putting [UX/Cloudscale Postdoc AutoCircuit] in the subject line or visit the University's HR website and search for Recruitment Reference #079228. All applications are handled centrally by the University's HR department.

Research Assistant / Postdoctoral Researcher (Level 1) – Electronic Design & Integration for AI-Driven Hardware Design (2 Positions)

Join the AutoCircuit project to help develop a cutting-edge tool that automatically generates digital circuits from high-level specifications. This is an exciting opportunity to work at the intersection of human-guided AI and hardware design, contributing to a novel toolchain that integrates with industry-standard Electronic Design Automation workflows.

Based at UL, you'll collaborate with a dynamic, interdisciplinary team funded by an Enterprise Ireland Commercialisation Award with the goal of forming a successful deep-tech company. This industry and spinout focused project will position you as a core member of the founding team, giving you the opportunity to secure a founder's equity position upon incorporation and significantly de-risking your entrepreneurial journey. The principal founders are all graduates of successful startups.

The successful candidates will contribute to the development of AutoCircuit, a next-generation system that automatically generates synthesizable Register Transfer Level (RTL) designs.

• The Backend Integration & Synthesis Validation role will ensure AutoCircuit outputs are robust, standards-compliant, and seamlessly integrated with commercial EDA flows across ASIC and FPGA platforms.
• The Frontend Development & System-Level Integration role will ensure AutoCircuit is practical and usable by focusing on FPGA deployment, user constraint interfaces, and debugging toolkits.

Both roles are key to validating AutoCircuit against real-world industrial design constraints and ensuring it delivers measurable impact for industry partners.

PhD Position – Trustworthy AI for Clinical Trials (1 Position)

Clinical trials remain difficult for patients to navigate. Eligibility criteria are complex, information is fragmented, and misunderstandings can directly impact recruitment, retention, and patient outcomes. This PhD project, Agentic AI for Clinical Trial Support, will focus on developing a trustworthy, multilingual large language model (LLM) that provides clear, plain-language explanations of clinical trial processes, including eligibility, risks, and expectations.

The objective is to improve how clinical trial information is communicated and understood in practice. A central aim is to investigate how agentic AI features such as structured reasoning, response provenance, and self-consistency can improve reliability, transparency, and user trust in healthcare settings. A particular focus will be on how these techniques perform in practice when applied to real-world clinical trial information, where ambiguity, complexity, and incomplete data are common.

The project sits at the intersection of artificial intelligence, digital health, and human-centred computing, contributing to emerging research in trustworthy AI and supporting alignment with European digital health priorities.

• A supportive and interdisciplinary research environment within CSIS and Lero
• Training in advanced machine learning and research methods
• Opportunities to publish and present at leading conferences

The ideal candidate will be a highly motivated and confident self-starter, capable of conducting independent research. We are seeking a candidate with:

• Minimum 2:1 degree in Computer Science or a related discipline.
• Demonstrable skills in large language models, natural language processing, or machine learning.
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Awareness of trustworthy and ethical AI concepts such as explainability, bias, and reliability.
• Strong communication and analytical skills.
• Evidence of practical coding or applied project experience, such as a GitHub profile, project portfolio, dissertation, or relevant software development work.

Preference will be given to candidates that can demonstrate one or more of the following:

• Exposure to digital health, healthcare applications, or clinical data.
• Experience with multilingual NLP.
• Familiarity with agentic AI, retrieval-augmented generation (RAG), or related LLM-based systems.
• Experience working with complex, incomplete, or real-world datasets.
• Interest in human-centred, safe, and transparent AI systems.

Please submit the following:

• A Curriculum Vitae (CV).
• A statement of purpose outlining your motivation, relevant experience, and career goals (maximum 500 words).
• One example of practical technical work relevant to deep learning, natural language processing, or large language models. This may be a GitHub repository, project portfolio entry, dissertation or thesis code, or a short technical summary of a completed project. It should briefly describe your role, the methods and tools used, the dataset or task addressed, and the outcome of the work (maximum 500 words).

To comply with University of Limerick requirements, applicants invited for interview will be required to submit academic transcripts (in English) and proof of English language proficiency. Applications should be sent to Dr. Alison O'Connor by 5pm July 30th 2026, with an expected project start date Q4 2026.