Research Software Engineer

ph3Build the science that shapes the future of human health. /h3h3Application closing date: /h3h3Join a place where ambitious science thrives /h3pHuman Technopole (Milan) is a rapidly expanding life science institute 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. /ppWithin this mission, the Ganna Group in the Health Data Science Centre, develops next generation AI methods to integrate population scale healthcare data with human genetics. The team comprises data scientists, biologists, and medical doctors, and is based across two locations: the Institute for Molecular Medicine Finland ( University of Helsinki) and Human Technopole. The lab has a strong track record of high impact publications. Our research increasingly relies on large and complex computational infrastructures. /ppWe are seeking a motivated bResearch Software Engineer /b who enjoys working at the interface between software engineering, artificial intelligence and biomedical research. You will support the activities of the Ganna Group in the Health Data Science Centre and you will work closely with researchers developing AI models using some of the worlds largest longitudinal health datasets, including nationwide data from Finland and France, as well as regional data from Lombardy. These resources comprise billions of healthcare events and can be linked with genetic and multi omics data. You will also benefit from collaborations with leading international institutions, including the University of Helsinki, ELLIS Institute Finland, EMBL-EBI, the Broad Institute of MIT and Harvard, and other global partners, providing valuable opportunities to engage with prominent research groups in machine learning, human genetics, and computational biology. /ph3Your mission /h3pAs a Research Software Engineer, you will be embedded directly within the research team, working closely with scientists developing innovative machine learning and statistical methods. Your role will combine the engineering standards of professional software development with the exploratory environment of cutting edge research. /ppYour responsibilities will range from developing pipelines to process population scale health data to supporting the training and evaluation of large foundation models and deploying research software across high performance computing and cloud environments. The scale and complexity of these datasets present unique engineering challenges, as our research draws on longitudinal health records comprising more than 5 billion medical events, FinnGen genetic data from over 500 000 individuals, and emerging multi omics resources, including proteomics and single cell RNA sequencing data. /ppSome projects will involve improving and scaling existing research code, while others will require designing new infrastructure from the ground up. You will have considerable autonomy in selecting the most appropriate technologies and will help establish software engineering standards across the lab. /ppDepending on your interests, you will also have opportunities to contribute intellectually to methodological projects and scientific publications. /ph3Grow Your Skills /h3pYou will enhance your scientific and professional skills by: /pulliDeveloping and maintaining scalable software and data pipelines for population scale health, genomic and multi omics data. /liliTurning research prototypes into reliable, reusable and well tested software. /liliSupporting the training, evaluation and deployment of large AI and foundation models across HPC, GPU and cloud environments. /liliEstablishing modern software engineering practices for reproducibility, testing, continuous integration, documentation and containerisation. /liliWorking closely with researchers and international collaborators to improve the efficiency, robustness and portability of computational methods. /li /ulpHuman Technopole supports career development through training, mentoring and dedicated learning opportunities. /ph3What you bring /h3ulliBSc, in computer science, software engineering, bioinformatics, computational science, or another relevant quantitative field. /liliStrong programming skills, particularly in Python, and experience developing maintainable software rather than only exploratory scripts. /liliExperience with modern software development practices such as Git, testing and continuous integration. /liliProfessional proficiency in English. /li /ulh3Preferred /h3ulliMSc or higher degree in computer science, software engineering, bioinformatics, computational science, or another relevant quantitative field. /liliExperience with working with large scale biomedical data: electronic health records, genetics, multi omics datasets. /liliExperience with machine learning frameworks applied in the context of biomedical data. /liliExperience with high performance, distributed or cloud computing, including GPU based environments. /li /ulh3Organizational and social skills /h3ulliAbility to work independently while collaborating with researchers from different scientific backgrounds. /liliAbility to work accurately, with attention to detail. /liliSelf motivated, able to work independently and organise own workload. /liliExcellent communication skills. /liliEnthusiastic team player and able to work collaboratively and across different disciplines. /li /ulh3Why Human Technopole /h3pHT offers an international and dynamic workplace, competitive welfare provisions, flexible working policies and relocation support. Researchers moving to Italy benefits from attractive tax benefits. We promote work-life balance and provide parental support initiatives. /ppThis is a fixed-term 4-year contract, with the possibility of extension, offered under CCNL Chimico Farmaceutico, level B2. /ppSalary: up to € 46k. /ppThe position is based in Milan, Italy, within our vibrant international campus. /ph3We strongly encourage applications from candidates belonging to protected categories (L. 68/99). /h3 /p #J-18808-Ljbffr