Data Scientist - Bioinformatician AI Center

Aimlroles; Rozzano; On-site; EUR 60,000 - 90,000; Full time

Job summary

Humanitas Research Hospital's AI Center seeks a motivated Bioinformatician/Data Scientist to join an interdisciplinary team as an independent researcher, focusing on rare hematological diseases and precision medicine.

You will work with clinical, -omics and imaging data to develop scalable multi-modal AI models and validate them clinically, collaborating with international partners to translate findings into actionable healthcare strategies.

Qualifications

• Master's or PhD in Bioinformatics or Computational Biology or related STEM field.
• Strong understanding of -omics data structures and analytical methods.
• Experience in data integration and multi-modal analysis.
• Proficiency in ML/DL techniques applied to healthcare data.
• Proficiency in Python/R and scripting platforms.
• Experience with containerization (Docker/Singularity) and cloud/HPC environments.
• Fluent in English and Italian.

Responsibilities

• Process and analyze clinical, -omics, and imaging data.
• Develop scalable AI models for personalized medicine.
• Research and validate multi-modal integrative models.
• Support clinical validation of AI/ML approaches.
• Collaborate with international partners on research projects.
• Deliver reproducible research and code.

Skills

Machine learning

Deep learning

Multi-modal data

Python

R

Docker

Singularity

Git

Cloud computing

HPC

English

Italian

Education

Master's or PhD in Bioinformatics/Computational Biology

Tools

Docker

Singularity

Git

GCP

AWS

HPC

Job description

We are looking for one highly motivated Bioinformatician/Data scientist with expertise in bioinformatics, machine and deep learning related areas to join our interdisciplinary group, as independent researcher.

As part of our technological team, we expect the candidate to help us discover the hidden information underlying complex data (clinical information, DNA-seq, RNA-seq, single-cell and histopathological medical image data), developing innovative multi-modal integrative and deep learning-based models able to translate research findings into personalized healthcare strategies. The common purpose leading the research activities is the progression toward a data-driven precision medicine with a main focus on rare hematological diseases.

The AI Center of Humanitas is focused in research in the field of Artificial Intelligence applied in healthcare. Research and development areas include predictive and decision-support systems based on data-driven model (ML/DL models) to optimize clinical processes and ultimately improve the quality of patient care. We are a team of multidisciplinary scientists who work day by day on e-health and AI projects, by collaborating with clinical staff (doctors, nurses, researchers) and management staff.

Responsibilities and Main Activities

• Processing and analysis of clinical, -omics and imaging data; harmonization of complex and highly fragmented data;
• Investigate, define and support the implementation of scalable computational models in order to extract relevant features for improving personalized medicine programs;
• Collaborate in research and development of innovative techniques for understanding disease-specific patterns from multi-modal and heterogeneous data;
• Explore, define and support the clinical validation of the statistical and AI/ML integrative models applied to real-world data;
• Contribute to solutions design and establishment of requirements;
• Visualize data, report effective results and derive useful knowledge using a data-driven approach;
• Self and team-management on individual and team-sized studies’ deadlines;
• Collaborate with international partners on cross-academic research projects.

Qualifications and required skills

• We invite applications from highly motivated and outstanding students with a Master Degree’s or PhD (preferably but not mandatory) in one of the following disciplines: Bioinformatics or Computational Biology, Biomedical Engineering or Computer Science or STEM related disciplines.
• Understanding of –omics data structures and modeling. Experience in -omics data analysis is preferably;
• Experience in developing algorithms for data integration investigating disease-specific relevant markers, exploring dimensionality reduction methods to identify latent patterns and key features for clinical process improvement;
• Good knowledge of machine learning and deep learning techniques (e.g. k-NN, SVM, Random Forests, CNN, autoencoders, etc.) applied to healthcare;
• Good knowledge of statistical methods applied to medical data;
• Good scripting and programming skills (R, Python, bash);
• Working knowledge of containers technologies (Docker and/or Singularity);
• Experience in cloud (GCP, AWS) and/or distributed computing (HPC) is appreciated;
• Experience in pipeline development, of reproducible research (e.g. git) and/or reproducible software development is a plus;
• Fluent in written and spoken English and Italian;

Soft Skills

• Excellent team-working capabilities even with colleagues from different research areas and backgrounds;
• Strong self-motivation, commitment and proactive approach;
• Ability to meet deadlines and work autonomously in rapidly changing environments;
• Curiosity and ability of stepping outside your comfort zone.

Why you should consider this opportunity

Humanitas Research Hospital is investing in data driven research and development of clinical support tools based on AI, you will contribute to the design and application of breakthrough technologies to be deployed in advanced clinical institutions.

You will get access to an extraordinary group of talented and passionate people coming from fields ranging from clinical sciences and healthcare management to informatics, bioinformatics and systems biology, including our extended international research network.

All candidate data collected from the application shall be processed in accordance with applicable law: Dlgs 198/2006 e dei Dlgs 215/2003 e 216/2003; privacy ex artt. 13 e 14 del Reg. UE 2016/679.