ppOrganisation/Company Istituto Italiano di Tecnologia Research Field Computer science Researcher Profile Recognised Researcher (R2) Application Deadline 1 Sep 2026 - 00:00 (UTC) Country Italy Type of Contract Other Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No /ph3Offer Description /h3pCommitment contract: 12 months (+12 renewable) /ppLocation: Genova /ppStep into a world of endless possibilities, together let’s leave something for the future! /ppAt IIT, we are committed to advancing human-centered Science and Technology to address the most urgent societal challenges of our era. We foster excellence in both fundamental and applied research, spanning fields such as neuroscience and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences, offering a truly interdisciplinary scientific experience. Our approach integrates cutting-edge tools and technology, empowering researchers to push the limits of knowledge and innovation. With us, your curiosity will know no bounds. /ppWe are dedicated to providing equal employment opportunities and fostering diversity in all its forms, creating an inclusive environment. We value the unique experiences, knowledge, backgrounds, cultures, and perspectives of our people. By embracing diversity, we believe science can achieve its fullest potential. /ppbTHE ROLE /b /ppYou will be working in a multicultural and multi-disciplinary group, where junior and senior scientists collaborate, each with their expertise, to carry out a scientific activity with shared research goals. The research focuses on fundamental AI topics from methodological and theoretical perspectives, yet functional to tackle a number of applications and actual case studies related to several domains. /ppThe Artificial Intelligence for Good (AIGO) research unit is coordinated and led by prof. Vittorio Murino. /ppAIGO benefits from the collaboration with several universities and research centres worldwide, most often with the closer universities of Genova and Verona. AIGO is part of ELLIS ( ) – an European network of excellence in AI, Machine Learning (ML) and Computer Vision (CV), of which Vittorio is a Fellow member. /ppFor this particular position, the focus is on investigating bAI approaches for physical and natural sciences /b, e.g., physics, chemistry, material science, weather forecast, biology, neuroscience, etc. Interestingly, these domains are characterized by the availability of huge amount of multimodal data (e.g., meteorological acquisitions, with radar scans and other ambient or physical parameters), and this makes AI techniques particularly convenient to use, since they are particularly data-hungry.



But many lines of research in these domains have been faced to date by designing particular simulation systems, mainly based on physical laws (e.g., differential equations). To this end, a possibility to be explored is the design of bhybrid /b simulation systems in which the rigor of physical laws is integrated with the power and versatility of AI methods trained with on-field data, either annotated or not. In this context, the fast development of always novel emgenerative /em models (from GANs to Flow Matching) will open other possibilities in the study of physical sciences’ applications. Finally, the data-agnostic nature of these models makes AI particularly suitable to cope with these issues, being possible to deal with multimodal data such as images, signals, strings, but also text. /ppAIGO is a perfect environment to study these topics given its expertise in Machine and Deep Learning, Computer Vision, Signal Processing, and Multimedia. Also, its declared vision to work especially in presence of bimperfect data /bandb multimodal /b setups – hence by tackling unsupervised, semi-supervised and self-supervised settings, weakly or noisy labeled, few, class imbalanced, or biased data – is exactly what it is needed to cope with these scenarios. emDomain adaptation, generalization /em, emfew/zero-shot learning /em, and open-set recognition, topics in which AIGO has contributed, also show to be particularly useful to tackle this type of problems. /ppWithin the research team, your main responsibilities will be: /pulliTo pursue research in some of the above mentioned interdisciplinary topics addressed by AIGO research line, at both individual and collaborative level. Interdisciplinarity research along IIT Flagship program “Teaching Science to Computers” is the main task for this position: material science, chemistry and neuroscience are to date the closest avenues to investigate, but other topics are not excluded, such as, e.g., physics and weather forecast. /liliSupervise the research activities of PhD students. /liliPublications on major conferences and top journals. /liliSearch and preparation of funding opportunities, e.g., project proposals to apply to national and international grants, as well as to acquire funds from industrial partners. /li /ulpbESSENTIAL REQUIREMENTS /b /pulliA PhD inMachine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas.



/liliDocumented expertise in:ulliMachine/Deep Learning, and possibly Computer Vision, with focus on multimodal learning; /liliDeep generative models, e.g., GANs, diffusion models, encoder-decoder architectures, optimal transport models, Flow Matching; /liliML and CV approaches with a preference for former and recent deep learning models (GNNs, Transformers, etc.). /li /ul /liliStrong programming ability (Python preferred) with hands-on skills in AI and Deep Learning frameworks (e.g., Pytorch, Tensorflow or equivalent tools). /liliSpouse the mainstream AIGO research line above quoted. /liliAbility/willingness to integrate within multidisciplinary research group. /liliProven strong track publications record in the relevant technical areas. /liliThe ability to properly report, organize and publish research data. /liliHigh motivation to learn. /liliGood priority management. /liliFluency in spoken and written English. /li /ulpbADDITIONAL SKILLS /b /pulliKnowledge/experience on multimodal approaches, and possibly on (some of) the topics above quoted (e.g., domain adaptation, few-shot learning, self-supervised learning, etc.). /liliExperience with deep learning approaches applied to different science domains, such as chemistry, materials, physics, imaging, drug discovery, climate/weather forecast, etc. /liliKnowledge of implicit deep learning models (NERF, neural rendering, Gaussian splatting, etc.). /liliKnowledge of graph neural networks. /liliExperience in deploying and fine-tuning DL models, also large language or vision-language models. /liliPractical experience on deploying ML models on HPC platforms. /liliTeam player skills with the ability to communicate technical knowledge in a clear and understandable manner. /liliCapacity to work autonomously and collaboratively in a challenging highly interdisciplinary environment. /liliPossess analytical reasoning skills and a growth mindset. /li /ulpbCOMPENSATION BENEFITS /b /pulliA yearly gross salary ranging between 35k€ and 45k€, which may include a premio option depending on your role and contract. /liliPrivate health care coverage depending on your role and contract. /liliWide range of staff discounts. /liliFlexible working time. /liliCandidates from abroad or Italian citizens who permanently work abroad and meet specific requirements, may be entitled to a deduction from taxable income of up to 90% from 6 to 13 years. /li /ulpemPlease submit your application using the online form and including: /em /pulliemA detailed CV with a full list of publications. Evidence of “Relevant skills” commenting on the strong points where your CV matches the required skills (listed above) will be appreciated. /em /liliemContact details of 2 references. /em /li /ul /p #J-18808-Ljbffr

📌 One Postdoctoral position on multimodal and generative AI for physical and natural sciences (Italia)
🏢 Istituto Italiano Di Tecnologia
📍 Italia