Machine Learning Scientist

Job Description

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This role is a remote Machine Learning Scientist contract position in the UK, lasting for an unspecified duration, offering competitive pay. Candidates must have a Ph.D. in a relevant field, 3-5+ years of industry experience, and expertise in generative modeling.

Location: Remote, United Kingdom.

What you will do

• Invent & deliver: Design, prototype, and productionize generative models for cellular level biological phenomena.
• Bridge research to product: translate promising prototypes into robust and well tested systems.
• Collaborate cross functionally: Foster strong collaboration with other team members.
• Lead innovation initiatives: Leading innovation initiatives and incorporating fresh ideas and technologies.

Job Requirements

• Must have a Ph.D. in Computer Science, Artificial Intelligence or related field.
• 3-5+ post Ph.D. years of industry experience building and deploying ML models.
• Demonstrated research excellence (e.g., strong publication record in top tier AI venues) and ability to convert insights into working systems.
• Depth experience in generative modeling. Good understanding of flow models a plus.
• Strong coding and problem solving skills.
• Excellent communication and collaboration skills, proven ability to work independently and collaboratively with minimal supervision.
• Passionate about addressing complex, real world challenges and creating impactful, innovative solutions.

How to apply

Interested candidates please submit your CV with a full list of your publications.

Synlico Inc. is a resident company of Johnson & Johnson Innovation - JLABS, a premier life science incubator program. Synlico envisions rewriting medicine by bringing causality to cellular biology. We are an AI-powered Drug Discovery startup developing cutting edge AI platform to combat diseases with the latest advancements in single cell bioinformatics, machine learning, and causal discovery. We are a passionate team of young scientists and professionals who value innovation and teamwork. Our research is highly interdisciplinary and team oriented. We are seeking a talented and enthusiastic machine learning scientist who will lead/participate in several of our projects with our science team. For more information, please visit .

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