Postdoc

Aretè & Cocchi Technology; Italia; In loco; EUR 35.000 - 45.000; Tempo pieno

Vantaggi offerti da questo lavoro

Private health care

Flexible working time

Staff discounts

Descrizione del lavoro

IIT's Artificial Intelligence for Good (AIGO) research unit invites applications for a postdoctoral position focused on multimodal and generative AI for physical and natural sciences. The postdoc will work in a multicultural team with senior and junior scientists to advance AI methodologies and their applications to diverse domains.

The role emphasizes exploration of hybrid data-driven and physics-informed approaches, with an emphasis on self-supervised and unsupervised learning, and close

Competenze

• PhD in Machine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas.
• Documented expertise in Machine Learning/Deep Learning with multimodal learning.
• Deep generative models (GANs, diffusion, encoder-decoder, Flow Matching).
• ML/CV approaches with emphasis on modern DL models (GNNs, Transformers).
• Strong programming ability (Python) with hands-on experience in PyTorch/TensorFlow.

Mansioni

• Pursue research in interdisciplinary topics within AIGO and IIT flagship activities.
• Supervise PhD students and contribute to mentoring.
• Publish in major conferences/journals.
• Identify and prepare funding opportunities for national and international grants.

Conoscenze

Machine Learning

Computer Vision

Multimodal Learning

Deep Learning

Python

PyTorch

Transformers

Research Publication

Formazione

PhD in Machine Learning/CS/Physics/Engineering

Strumenti

PyTorch

TensorFlow

HPC frameworks

Descrizione del lavoro

One Postdoctoral position on multimodal and generative AI for physical and natural sciences

Italy

Commitment & contract: 12 months (+12 renewable)

Location: Genova

Step into a world of endless possibilities, together let’s leave something for the future!

At 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.

We 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.

THE ROLE

You 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.

The Artificial Intelligence for Good (AIGO) research unit is coordinated and led by prof. Vittorio Murino.

AIGO 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 (https://ellis.eu/ ) – an European network of excellence in AI, Machine Learning (ML) and Computer Vision (CV), of which Vittorio is a Fellow member.

For this particular position, the focus is on investigating AI approaches for physical and natural sciences, 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 hybrid 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 generative 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.

AIGO 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 imperfect data and multimodal 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. Domain adaptation, generalization, few/zero-shot learning, and open-set recognition, topics in which AIGO has contributed, also show to be particularly useful to tackle this type of problems.

Within the research team, your main responsibilities will be:

• To 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.


• Supervise the research activities of PhD students.


• Publications on major conferences and top journals.


• Search 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.

ESSENTIAL REQUIREMENTS

• A PhD inMachine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas.


• Documented expertise in:
  
  
  
  • Machine/Deep Learning, and possibly Computer Vision, with focus on multimodal learning;
  
  
  • Deep generative models, e.g., GANs, diffusion models, encoder-decoder architectures, optimal transport models, Flow Matching;
  
  
  • ML and CV approaches with a preference for former and recent deep learning models (GNNs, Transformers, etc.).
  
  
  
  


• Strong programming ability (Python preferred) with hands-on skills in AI and Deep Learning frameworks (e.g., Pytorch, Tensorflow or equivalent tools).


• Spouse the mainstream AIGO research line above quoted.


• Ability/willingness to integrate within multidisciplinary research group.


• Proven strong track publications record in the relevant technical areas.


• The ability to properly report, organize and publish research data.


• High motivation to learn.


• Good priority management.


• Fluency in spoken and written English.

ADDITIONAL SKILLS

• Knowledge/experience on multimodal approaches, and possibly on (some of) the topics above quoted (e.g., domain adaptation, few-shot learning, self-supervised learning, etc.).


• Experience with deep learning approaches applied to different science domains, such as chemistry, materials, physics, imaging, drug discovery, climate/weather forecast, etc.


• Knowledge of implicit deep learning models (NERF, neural rendering, Gaussian splatting, etc.).


• Knowledge of graph neural networks.


• Experience in deploying and fine-tuning DL models, also large language or vision-language models.


• Practical experience on deploying ML models on HPC platforms.


• Team player skills with the ability to communicate technical knowledge in a clear and understandable manner.


• Capacity to work autonomously and collaboratively in a challenging highly interdisciplinary environment.


• Possess analytical reasoning skills and a growth mindset.

COMPENSATION & BENEFITS

• A yearly gross salary ranging between 35k€ and 45k€, which may include a bonus option depending on your role and contract.


• Private health care coverage depending on your role and contract.


• Wide range of staff discounts.


• Flexible working time.


• Candidates 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.

Application’s deadline: September 1st, 2026

To discover more about life at IIT, visit the dedicated section here:https://www.iit.it/en/work-at-iit