Research Scientist (Ai)
Pubblicato il 20-08-2026 - Arsenale BioYards in Pordenone
About Arsenale Bioyards Arsenale is reimagining industry for the neo-industrial age — building a new production infrastructure grounded in biology, intelligence, and regeneration. Our proprietary platform unites precision fermentation, advanced hardware, sensing, and AI to enable nature-aligned manufacturing at scale. We are a collective of neo-industrialists — curious, critical minds united by a commitment to reshaping how the world makes things. International by nature, we work across disciplines and borders, bound by shared values. English is our corporate language. If you're drawn to systems thinking, deep complexity, and the possibility of building something fundamentally new — we'd like to meet you. The Opportunity To help us reach this goal, we seek multiple highly skilled Research Scientists to join the Data and AI team. These are high-impact roles at the core of our AI efforts, ideal for individuals with a strong background in machine learning and a passion for solving real-world scientific and engineering challenges. Role Purpose Your Impact
- Working closely with interdisciplinary teams, from fermentation scientists to microbiologists
- Bringing data-driven perspectives to complex problems
- Communicating with non-technical stakeholders to translate technical insights
- Developing and deploying AI systems that support Arsenale's bio-manufacturing platform
- Contributing to scientific research and publications that advance the field Essential skills
- PhD in machine learning, computer vision, NLP, or related fields.
- Excellent proficiency in Python and PyTorch.
- Strong analytical and problem-solving skills.
- Excellent English communication skills. Adaptive qualities
- Collaborative mindset for working in cross-functional teams
- Strong analytical and problem-solving approach
- Excellent communication skills for technical and non-technical audiences
- Adaptability to work across diverse scientific domains Nice to have
- Experience working in cross-functional teams.
- Impactful publications (we encourage publishing).
- Open source contributions.
- Experience with probabilistic programming frameworks (e.g. Pyro, pymc, Stan, etc.).
- Background in stochastic processes.