RNA-Seq Deep Learning Scientist for Cancer Genomics

1000scholars; Milano; On-site; EUR 41,000 - 50,000; Full time

Job summary

IEO - European Institute of Oncology in Milan, Italy, seeks a Deep Learning Scientist to design CNN and Vision Transformer models that operate directly on RNA-seq data to detect expressed mutations. The role interfaces with bioinformatics and ML teams to benchmark performance and integrate calls into predictive pipelines.

The project emphasizes RNA-driven cancer genomics and immuno-oncology, with opportunities to contribute to scientific publications and software documentation.

Qualifications

• Strong Python programming and data analysis skills.
• Experience with PyTorch or TensorFlow and CNN/Transformer models.
• Familiarity with RNA-Seq / DNA-Seq workflows and variant calling pipelines.

Responsibilities

• Develop and optimize deep learning architectures for RNA-seq–based variant calling.
• Adapt and extend CNN- and ViT-based frameworks for RNA-specific mutation detection.
• Benchmark RNA-based variant calls against DNA-seq ground truth datasets.

Skills

Python

NumPy / Pandas / SciPy

Linux HPC

PyTorch / TensorFlow

CNNs / Transformers

RNA-seq data representations

Education

PhD or Master’s in a quantitative field

Tools

STAR

GATK

samtools

bcftools

Job description

IEO - European Institute of Oncology in Milan, Italy, seeks a Deep Learning Scientist to design CNN and Vision Transformer models that operate directly on RNA-seq data to detect expressed mutations. The role interfaces with bioinformatics and ML teams to benchmark performance and integrate calls into predictive pipelines.

The project emphasizes RNA-driven cancer genomics and immuno-oncology, with opportunities to contribute to scientific publications and software documentation.