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Arsenale BioYards is building a new production infrastructure grounded in biology, intelligence, and regeneration. The company's proprietary platform unites precision fermentation, advanced hardware, sensing, and AI to enable nature-aligned manufacturing at scale. They are seeking multiple Research Scientists to join the Data and AI team in high-impact roles at the core of their AI efforts.
As a Research Scientist, you will lead projects involving the application of machine learning solutions across diverse domains within the company. You will work closely with interdisciplinary teams, including fermentation scientists and microbiologists, to bring data-driven perspectives to complex problems. Key responsibilities include:
- Leading projects involving machine learning solutions across diverse scientific and engineering domains
- Working closely with interdisciplinary teams (fermentation scientists, microbiologists, and others)
- Bringing data-driven perspectives to complex problems
- Communicating technical insights to non-technical stakeholders
- Developing and deploying AI systems that support Arsenale's bio-manufacturing platform
- Contributing to scientific research and publications that advance the field
The role is ideal for individuals with a strong background in machine learning and a passion for solving real-world scientific and engineering challenges. Arsenale is international by nature, with English as the corporate language. The company values systems thinking, deep complexity, and collaborative problem-solving across disciplines and borders.
REQUIREMENTS:
- 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 for both technical and non-technical audiences
- Scientific curiosity and passion for applying machine learning to real-world challenges
- Collaborative mindset for working in cross-functional teams
- Adaptability to work across diverse scientific domains
NICE TO HAVE:
- Experience working in cross-functional teams
- Impactful publications (company encourages publishing)
- Open source contributions
- Experience with probabilistic programming frameworks (Pyro, pymc, Stan, etc.)
- Background in stochastic processes
