Computational Biologist/ML Engineer

About Viantis Viantis is developing next-generation Viral-targeting nucleotides. We combine molecular biology, computational biology, AI, and experimental validation to identify and optimize novel therapeutic candidates targeting conserved viral structures.

Role Overview We are seeking an experienced

Computational Biologist/ML Engineer

to lead the computational aspects of our discovery platform. The ideal candidate will have a strong background in computational biology, bioinformatics, and machine learning applied to biological systems, with a proven track record of working on real-world scientific problems. This is a hands-on role focused on target identification, structural analysis, sequence modeling, and AI-driven candidate prioritization, working closely with our experimental team. The successful candidate will play a key role in building the company's proprietary computational discovery platform and translating experimental data into actionable scientific insights.

Responsibilities Design and develop proprietary computational workflows for biological target identification and candidate prioritization. Build software platforms integrating biological data, machine learning models, and experimental results. Develop predictive models for candidate ranking, performance prediction, and decision support. Implement active learning, optimization, and data-driven iterative improvement frameworks. Create robust data pipelines for processing, analyzing, and visualizing complex biological datasets. Develop internal dashboards, reporting systems, and research productivity tools. Collaborate closely with experimental scientists to integrate computational and laboratory workflows. Contribute to the long-term architecture and strategy of the company's computational platform.

Must Have (DO NOT APPLY IF YOU ARE NOT MATCHING AT LEASTN 6 OUT OF 8 POINTS) MSc or PhD in Computational Biology, Bioinformatics, Systems Biology, Machine Learning, Computational Chemistry, Data Science, or a related field. At least 4–5 years of hands-on experience

applying computational methods to biological or biomedical problems. Strong programming skills (Python preferred) Experience developing production-quality software and scientific data pipelines. Experience with machine learning frameworks and modern AI methodologies. Familiarity with biological sequence analysis, molecular datasets, or related life-science applications. Ability to work independently and translate scientific objectives into computational solutions. Located in Trieste (Ideally) or Eurozone

Contract 1 year with possibility of conversion to permanent contract. 2-month probation period, Full time, Competitive salary + stock options depending on experience and fit.