Institution: Human Technopole
Centre: Health Data Science Centre (HDS Centre)
Research Group: Di Angelantonio–Ieva Group
Location: Milan, Italy
Contract Type: Full-time Postdoctoral Position
Duration: 4 years
Salary: Up to €50,000 per year (commensurate with seniority)
Application Deadline: 21 February 2026

Build the Science That Shapes the Future of Human Health

Human Technopole (HT) is a rapidly expanding life science institute in Milan, where international researchers and cutting-edge technologies converge to accelerate biomedical discovery. Our mission is to transform bold scientific ideas into advances that improve human health.

Within this mission, the Health Data Science Centre (HDS Centre) developed in partnership with Politecnico di Milano aims to deliver a step-change in health data science in Italy by systematically generating, integrating, and analyzing large-scale biomedical and health-related data to better understand the molecular, clinical, behavioural, and environmental determinants of non-communicable diseases.

Position Overview

We are seeking an ambitious Postdoctoral Researcher in Generative Machine Learning for Biomedical Data to support and expand the activities of the Di Angelantonio–Ieva Group within the HDS Centre.

This position is ideal for candidates interested in developing state-of-the-art generative machine learning models and applying them to large-scale biomedical, genomic, and clinical datasets, with direct relevance to precision medicine and disease trajectory modeling. The work is expected to lead to high-impact scientific publications.

Your Mission

As a Postdoctoral Researcher, you will focus on developing and applying advanced generative modeling approaches, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and transformer-based architectures, to complex biomedical datasets.

Your research will address challenges such as:

• Privacy-preserving generation of realistic biomedical and clinical data

• Modeling disease trajectories and predicting clinical outcomes

• Representation learning and exploration of latent spaces to uncover biological and clinical insights

You will work in a highly interdisciplinary environment, collaborating closely with geneticists, molecular epidemiologists, clinicians, and data scientists.

Key Responsibilities

• Design, develop, and lead analyses using state-of-the-art generative machine learning models applied to large-scale biomedical data

• Build and optimize pipelines for pre-processing, integrating, and modeling heterogeneous data sources, including genomic data, clinical event sequences, and disease codes

• Develop generative models to simulate patient health trajectories, disease progression, and clinical outcomes

• Apply transformer-based architectures to time-ordered clinical data for disease evolution prediction

• Collaborate across disciplines to design robust, scalable machine learning frameworks for precision medicine

• Interpret results and communicate findings through manuscripts, presentations, and reports

• Contribute to grant writing and the development of new research projects and pilot studies

• Prepare high-quality visualizations and summaries for scientific and public dissemination

• Promote open science, ethical research practices, and data governance standards

• Contribute to training activities (workshops, tutorials) and supervise MSc and PhD students, as appropriate

• Engage in public outreach and science communication initiatives

What You’ll Bring

Essential Qualifications

• PhD in Computer Science, Data Science, Mathematics, Engineering, or a closely related field (completed or expected within 6 months)

• Strong understanding of generative machine learning models (e.g., VAEs, GANs, transformers)

• Experience applying machine learning to biomedical, biological, or clinical data

• Proficiency in Python and modern machine learning frameworks

• Strong quantitative and analytical skills, including representation learning and sequence modeling

• Proven record of peer-reviewed scientific publications

• Fluency in English

Preferred Qualifications

• Prior experience applying generative models to biomedical, genomic, or clinical datasets

• Experience in disease trajectory prediction, synthetic patient generation, or health outcome modeling

Organizational and Interpersonal Skills

• High level of accuracy and attention to detail

• Self-motivated and able to work independently

• Excellent communication skills

• Strong collaborative mindset and enthusiasm for interdisciplinary research

Why Human Technopole

Human Technopole offers:

• An international, dynamic research environment

• Competitive welfare provisions and flexible working policies

• Relocation support and attractive Italian tax benefits for international researchers

• Strong commitment to work–life balance, parental support, and career development

How to Apply

Please submit the following documents in English:

• Curriculum Vitae (CV)

• Motivation Letter

• Contact details of two referees

📅 Application deadline: 21 February 2026

Contract Details

• 4-year contract under CCNL Chimico Farmaceutico

• Employee Level B2

• Salary up to €50,000 per year, depending on seniority

• Position based in Milan, Italy

Human Technopole strongly encourages applications from candidates belonging to protected categories (L. 68/99).

Apply Now!

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