Machine Learning and Researcher and Project Leader

As a researcher, you will initiate and work on innovative data-driven solutions in the bioeconomy and food domains. Your duties and responsibilities include:

• Initiating new projects and ideas for acquisition by shaping new applied research propositions and supplying insights to convey the value of AI solutions to partners and clients.
• Leading projects where you and your team design and develop new AI solutions, including translating research questions into robust machine learning implementations (preprocessing, model training, validation, and deployment).
• Collaborating enthusiastically with domain specialists and software developers to integrate data-driven models with mechanistic or physics-based models and domain expertise.
• Demonstrating thought leadership on applying data and AI solutions in the food and biobased domain.

What they ask

• Solid experience with AI- and machine learning-based approaches.
• Comfortable explaining complex technical concepts to non-technical stakeholders.
• Proactive, innovative, and a strong team player.
• A PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related field.
• At least 3 years of hands-on experience in AI/machine learning development (excluding PhD).
• Proven expertise in machine learning and generative AI methodologies (e.g., LLMs, RAG systems, agentic AI, feature engineering, model selection and validation, supervised and unsupervised learning, optimization techniques, (deep) neural networks, probabilistic methods and statistics, data visualization, natural language processing).
• Experience or strong affinity with incorporating domain knowledge and constraints into data-driven models (Hybrid Modelling). Knowledge and experience in food and biobased domains is a plus.
• Proficiency in Python and modern machine learning development, including version control (Git), testing, and reproducibility. Experience with cloud-based solutions (e.g., Azure) is a plus.
• C1 level of proficiency in English.

• Discussable working hours for an optimal work-life balance.
• Sabbatical leave, study leave, and partially paid parental leave.
• Strong focus on vitality with access to campus sports facilities for a small fee.
• Fixed year-end bonus of 8.3%.
• Excellent pension scheme.
• Initially a one-year contract, with the possibility of extension based on good performance.