ph3Research Software Engineer for Translational Biomedical AI /h3 h3Build the science that shapes the future of human health.br/Application closing date: /h3 h3Join a place where ambitious science thrives /h3 pHuman Technopole 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. /p pWithin this mission, the Health Data Science Centre develops advanced computational and machine learning approaches to analyse complex biomedical and clinical data. The Centre works at the interface of data science, machine learning, computational biology, epidemiology, and clinical research, with the goal of transforming research models into tools that can support biomedical discovery and healthcare innovation. /p pWe are seeking a motivated bResearch Software Engineer /b to help translate research prototypes into robust, usable, and transferable software tools. We welcome candidates at different levels of seniority. Depending on the selected candidate’s experience, the position may be shaped as either a Junior or as a Senior Software Engineer. /p pThis role sits at the interface between software engineering, machine learning and clinical translation. The successful candidate will work closely with data scientists, computational biologists, clinicians, ICT experts, and hospital partners to develop software systems that make advanced research models usable in real‑world biomedical and healthcare settings. This position is funded by the European Union EU4H-2026-SANTE-PJ-04 – Project: European Cardiovascular Health data and AI Network (CHAIN), GA . /p h3Your mission /h3 pAs a Research Software Engineer for Translational Biomedical AI, you will work closely with data scientists, computational biologists, clinicians, ICT experts, and external collaborators to make biomedical machine learning models easier to use, test, and share across research environments. /p pYou will help researchers turn prototype code, trained models, and analysis pipelines into software that is more maintainable, reproducible, documented, and portable. You will contribute to software tools that can: /p ul liTransform research code into maintainable and documented software. /li liPackage trained models and inference pipelines for deployment in external organizations. /li liEnable hospitals and collaborators to test models locally on their own data without transferring sensitive patient-level information. /li liSupport reproducible model evaluation across sites. /li liProvide usable interfaces, APIs, dashboards, or command-line tools depending on project needs; /li liensure that software tools are robust, secure, documented, and maintainable. /li /ul pThe role is not primarily a machine learning research position,



but the candidate should have enough understanding of machine learning workflows to work effectively with researchers developing predictive, generative, and analytical models for biomedical and clinical data. /p h3Grow your skills /h3 pYou will enhance your professional skills by contributing to: /p h3Research software engineering for biomedical AI /h3 ul liRefactoring and modularising scientific Python code. /li liTurning research prototypes into robust, reusable, and documented software. /li liSupporting reproducible model training, validation, inference, and reporting. /li liWorking with researchers to translate scientific requirements into software tools. /li liDeveloping tools that allow researchers, clinicians, and collaborators to interact with biomedical AI models in a controlled and usable way. /li /ul h3Machine learning model packaging and deployment /h3 ul liPackaging trained models, preprocessing pipelines, configuration files, metadata, and evaluation scripts into portable software artifacts. /li liDeveloping containerized model environments using Docker and related technologies. /li liBuilding reproducible inference pipelines that can be transferred to hospitals or external research organizations. /li liSupporting privacy-aware validation scenarios where models are tested locally without transferring sensitive data. /li liBuild CICD pipelines to support the software and AI models development life cycle, from development to testing and deployment. /li /ul pHuman Technopole supports career development through training, mentoring, and dedicated learning opportunities. /p h3What you’ll bring /h3 h3Essential /h3 ul liDegree in Computer Science, Software Engineering, Data Science, Bioinformatics, or equivalent professional experience. /li liExperience in software development, research software engineering, machine learning engineering, data science, or similar roles. /li liStrong programming skills in Python. /li liFamiliarity with scientific or machine learning Python libraries, such as NumPy, pandas, scikit-learn, PyTorch, TensorFlow, or similar. /li liExperience writing modular, maintainable, and documented code. /li liFamiliarity with Git and collaborative software development practices. /li liFamiliarity with machine learning workflows, including preprocessing, model inference, model evaluation, reproducibility, and experiment configuration. /li liExperience packaging software, models, or computational workflows for reuse by other users. /li liFamiliarity with containerization technologies such as Docker. /li liGood English communication skills, both written and spoken.



/li /ul h3Preferred /h3 ul liExperience with MLOps, model packaging, or deployment of machine learning models in research, clinical, or semi-production environments. /li liExperience with automated testing and simple CI workflows. /li liExperience developing APIs, command-line tools, dashboards, or lightweight web interfaces. /li liExperience with workflow management tools such as Nextflow, Snakemake, Airflow, or similar. /li liFamiliarity with secure or privacy-aware analysis workflows. /li liFamiliarity with biomedical data, longitudinal clinical data, EHRs, or hospital research environments. /li liExperience with cloud, institutional HPC, or hybrid computing environments. /li liFamiliarity with Kubernetes or production deployment environments. /li liExperience contributing to open-source scientific software or collaborative research software projects. /li /ul h3Organizational and social skills /h3 ul liStrong communication skills, given the multicultural and multidisciplinary nature of the team (including data scientists, biomedical researchers, clinicians, software engineers, and ICT experts). /li liAbility to translate between research needs, clinical requirements, and software implementation. /li /ul ul liStrong problem-solving skills, a proactive approach and ability to work across research, technical, and clinical domains. /li /ul ul liExcellent teamwork skills. /li liAbility to write clear technical documentation for both technical and non-technical users. /li liInterest in biomedical research and in the translation of AI methods into tools that can support real‑world health research. /li liAbility to balance the flexibility required in research with the robustness required for usable software. /li /ul h3Why Human Technopole /h3 pHuman Technopole offers an international and dynamic workplace, competitive welfare provisions, flexible working policies, and relocation support. Candidates moving to Italy may vantaggi from attractive tax benefits. We promote work–life balance and provide parental support initiatives. /p pThis position offers the opportunity to work at the interface of advanced machine learning, biomedical research, software engineering, and clinical translation. The successful candidate will contribute to tools that help make complex AI models usable, testable, and transferable across research and healthcare settings. /p pWe strongly encourage applications from candidates belonging to protected categories (L. 68/99) /p pFoundation reserves the right, at its sole discretion, to extend, suspend, modify, revoke, or cancel this job posting without giving rise to any rights or claims whatsoever in favor of the candidates; the Foundation reserves, however, the right not to proceed with the awarding of the above-described assignment due to the effect of supervening regulatory provisions and/or obstructive circumstances. /p /p #J-18808-Ljbffr

📌 Research Software Engineer for Translational Biomedical AI (Italia)
🏢 Human Technopole
📍 Italia