Key Skills

Job Description

ProQR Therapeutics is a NASDAQ-listed biotechnology company headquartered in Leiden, the Netherlands with an office in and Cambridge, Massachusetts, USA. At ProQR, we are on a mission to edit RNA, treat disease and change lives. A team of 180+ enthusiastic ProQRians from all walks of life and more than 30 different nationalities is committed to pioneering transformative RNA therapies to make a difference in the lives of the communities we serve. Our proprietary Axiomer™ RNA editing technology platform enables the editing of specific single nucleotides in RNA using the cells own editing machinery. Axiomer RNA editing technology harnesses ADAR (Adenosine Deaminase Acting on RNA), a protein which is present in all human cells, to repair G-to-A mutations, modulate protein, and enable protective mutation functions. Axiomer could potentially yield a new class of innovative medicines and treat currently untreatable diseases. By harnessing the power of RNA editing, we aim to create a world where genetics inform your health - but never limit it. Our R&D department is currently looking for an experienced ML Engineer - AI & Bioinformatics to join our team in Leiden. The ML Engineer will contribute to the development of robust, scalable pipelines that transform complex experimental biology data into AI-ready datasets. This role supports both scientific modeling initiatives and the automation of critical bioinformatics workflows, contributing to a standardized and reproducible data infrastructure. This position is ideal for someone with a strong foundation in machine learning and data engineering who is eager to apply those skills to real-world biological challenges and data-driven decision-making. You will work closely with laboratory and computational scientists, bioinformaticians and domain experts to ensure seamless integration of data and models. We expect our ML Engineer to have: MSc in Computer Science, Data Science, or a related quantitative discipline At least 2 years of relevant work experience in Machine learning, Generative AI models, Deep learning, or Data engineering (industry or advanced academic research) Strong proficiency in Python for data processing, scripting, and model development Practical experience with JAX or PyTorch for training and evaluating machine learning models Basic understanding of molecular biology plus willingness to learn RNA editing and oligonucleotide concepts on the job Hands-on experience with Linux-based environments and command-line tool. Familiarity with Docker (strongly preferred) or similar containerization tools for reproducible environments Demonstrated experience or interest in handling biological datasets Knowledge of software engineering best practices, including version control (Git), modular code design, and documentation Exposure to R for statistical workflows Curiosity and adaptability to explore the best tools and approaches for each project Preferred: Experience with foundation models, such as pre-training, fine-tuning, or applying large sequence models (biological or otherwise) Experience with active learning, Bayesian optimization, or other sequential experimental design methods Key Responsibilities: Design editing oligonucleotide (EON) candidates using ML models in a lab-in-the-loop cycle: propose sequences for synthesis and testing, incorporate the new experimental results, and iteratively improve both the models and the designs Develop, train, and evaluate AI models using JAX or PyTorch for biological prediction and design tasks in RNA therapeutics Adapt and fine-tune foundation models for downstream tasks, and explore new architectures and methods from literature Benchmark model performance across diverse biological tasks and contribute to model selection and improvement Work with wet-lab teams to plan design-test-learn rounds, including selecting which candidates to test so each round is as informative as possible Design, build, and maintain modular, reproducible data pipelines that transform raw experimental data into standardized, AI-ready datasets Automate and optimize data flows to reduce manual steps and improve scalability, using scripting and containerized tools (e.g., Docker) Collaborate cross-functionally with domain scientists, bioinformaticians, and project leads to align computational outputs with experimental context Contribute to data infrastructure initiatives, including FAIR-compliant schema development, metadata standards, and platform integration Support statistical analyses and data exploration using Python and/or R Ensure reproducibility through modular code design, version control (Git), thorough documentation, and adherence to best practices Engage in technical discussions, retrospectives, and team knowledge-sharing sessions to foster learning and continuous improvement Skills and competencies that are required for making the difference: Analytical and accurate Creative thinker Flexible and adaptable Hands-on mentality Proactive and pragmatic self-starter, with a result-oriented mindset Team player Autonomous and coachable Being able to work in a fast-paced environment Being able to prioritize multiple tasks Patient-oriented attitude Excellent knowledge of spoken and written English A nice person 😊 ProQR as an employer As an employer, we value a diverse workforce in which people are encouraged to develop themselves both personally and professionally. We believe that when people are happy, energized and supported by an environment in which they can thrive, they can achieve extraordinary things. We are committed to ensuring that no employee, candidate, or job applicant receives less favorable treatment on the grounds of race, age, disability, pregnancy, religion, gender identity and expression, sexual orientation, marriage or civil partnership status. At ProQR we want to create an inclusive culture where everyone can be valued for who they are and in which individual differences and contributions in all forms are recognized and valued. We offer an exciting and innovative working environment in a very committed organization, with the following benefits: 8% holiday allowance 30 vacation days An annual performance bonus Stock options A premium-free pension plan A commuting allowance A subsidized staff restaurant Unlimited (un) healthy snacks and drinks Employee events (boot camp, Coffee and Collaboration Café and other social events) We are looking for people who are inspired by our mission to edit RNA, treat disease and change lives. Are you up for the challenge? Submit your application via the Apply button below. Please contact Silvia Catellani via [email protected] if you have any questions.

Core Responsibilities

Develop and evaluate machine learning models for RNA therapeutic prediction and design, including adapting foundation models and iteratively improving oligonucleotide candidates through lab-in-the-loop experiments. Build reproducible, scalable pipelines that convert experimental data into standardized AI-ready datasets, while collaborating with laboratory and computational teams and supporting data infrastructure and statistical analysis.

Requirements

Requires an MSc in Computer Science, Data Science, or a related quantitative discipline, at least two years of relevant experience, and strong Python skills with practical JAX or PyTorch experience. Candidates should have Linux and command-line experience, familiarity with Docker, software engineering and version-control practices, an understanding of molecular biology or willingness to learn, and an interest in biological datasets; R exposure is also noted.

Benefits

• Holiday Allowance
• 30 Vacation Days
• Annual Performance Bonus
• Stock Options
• Premium-Free Pension Plan
• Commuting Allowance
• Subsidized Staff Restaurant
• Unlimited Snacks and Drinks
• Employee Events