AI-Driven Molecular Medicine Data Scientist

University of Helsinki; Helsinki; On-site; EUR 52,000 - 82,000; Full time

Job summary

The University of Helsinki invites applications for a Data Scientist or Biomolecular Scientist to join the DAIMM project in the Life Sciences. The role blends AI-driven data analysis, code development and collaboration with biologists, clinicians and computational researchers in a leading Nordic university.

You will work at FIMM, HiLIFE and Helsinki Institute of Life Science, contributing to generative AI research, multi-omics integration, and data pipelines.

Qualifications

• Strong understanding of biology, molecular medicine or related biomedical discipline with experience in computational analysis of biological data.

Responsibilities

• Develop AI-driven and computational approaches for analyzing large-scale biological, molecular and clinical datasets.
• Explore the use of generative AI, large language models, and AI agents.
• Develop data infrastructure, databases, software tools, APIs, and computational pipelines.
• Collaborate with biological, computational, and clinical researchers to connect computational approaches with experimental and medical research.

Skills

Python or R programming

Data analysis

Generative AI concepts

Machine Learning basics

Education

MSc in Biology

MSc in Molecular Medicine

MSc in Bioinformatics

MSc in Computational Biology

MSc in Computer Science

MSc in Data Science

MSc in Software Engineering

PhD or equivalent

Tools

Databases

Data pipelines

Single-cell data analysis

Spatial omics analysis

Genomics

AI/ML tools

Job description

The University of Helsinki invites applications for a Data Scientist or Biomolecular Scientist to join the DAIMM project in the Life Sciences. The role blends AI-driven data analysis, code development and collaboration with biologists, clinicians and computational researchers in a leading Nordic university.

You will work at FIMM, HiLIFE and Helsinki Institute of Life Science, contributing to generative AI research, multi-omics integration, and data pipelines.