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GelderlandHybrid36 hours/week<3months
As an experienced professional in machine learning and data science, you will contribute to a more sustainable and better world by applying advanced AI solutions. You will initiate and develop innovative data-driven solutions within the bio-economy and food domains.
What you will do.
- Initiate and develop innovative data-driven solutions.
- Improve processes such as fermentation screening for plant-based ingredients by applying machine learning to historical experimental data.
- Utilize large language model (LLM) tools to automatically unlock, structure, and make fragmented information from internal and external sources available for use in digital solutions.
- Initiate new projects and ideas for acquisition by shaping new applied research propositions and providing insights to convincingly convey the added value of AI solutions to partners and clients.
- Lead projects in which you and your team design and develop new AI solutions.
- Translate research questions into robust machine learning implementations, including data preprocessing, model training, validation, and implementation.
- Enthusiastically collaborate with domain specialists and software developers to integrate data-driven models with mechanistic or physical models and domain knowledge.
- Provide direction for the application of data and AI solutions within the food and biobased domain.
Profile
- Extensive experience with AI and machine learning methods.
- Easily connect with colleagues from other disciplines and be energized by the dynamics of multidisciplinary collaboration.
- Able to explain complex technical concepts to non-technical stakeholders and translate digital methods into practical and usable solutions.
- Proactive, innovative, and a true team player.
- PhD in Artificial Intelligence, Machine Learning, Computer Science, or a comparable field.
- Minimum of 3 years of demonstrable, hands-on experience with AI and machine learning development, excluding your PhD.
- Demonstrable expertise in machine learning and generative AI methodologies, including 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, and natural language processing.
- Experience with or a strong affinity for integrating domain knowledge and boundary conditions into data-driven models (Hybrid Modelling).
- Knowledge and experience within the food and biobased domains is a plus.
- Proficient in Python and modern methods for machine learning development, including version control (Git), testing, and reproducibility.
- Experience with cloud solutions, such as Azure, is a plus.
- English language proficiency at C1 level.
Practical
- Working hours can be set in consultation to allow for an optimal work-life balance.
- Opportunities for sabbatical leave, study leave, and partially paid parental leave.
- Focus on vitality and access to sports facilities.
- Encouragement of development and mobility within the organization.
How to apply
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