Work at the Leonardo Labs

In this research area, Leonardo is looking for researchers who have gained scientific work experience in one or more of the following domains: 

1. High Performance Computing: Porting, profiling, optimization and parallelization of scientific and industrial code on heterogeneous HPC infrastructures (CPUs, GPUs), development and implementation of new capabilities based on parallel algorithms and innovative computational methods;
2. Hardware / Software Co-design: Validation and evaluation of scientific and industrial codes performance on different hardware architectures, either already existing or experimental (e.g. RISC-V processors), in the context of Supercomputing and Edge Computing;
3. Cloud Computing: Instances creation and management on Cloud Computing infrastructures, Cloud services applications containerization, container deployment via orchestration tools, implementation of Data Lakes infrastructures.

Requirements for participation in the selection process:

• Experience working in Linux environments and High Performance Computing skills in code development and optimization (compilers, profilers, debuggers, git, cmake);
• Familiarity with methods for validating and evaluating the performance of scientific code, in particular parallel codes (e.g. strong and weak scaling);
• Knowledge of parallel programming algorithms and techniques in various hardware environments (shared memory, distributed memory, GPU acceleration);
• Knowledge of programming languages for scientific computing (C, C++, Fortran, Python), parallel programming paradigms on CPU and GPU (MPI, OpenMP, OpenACC, CUDA), languages for heterogeneous architecture (SYCL);
• Experience with Edge Computing paradigms and their methodologies;
• Familiarity with different application containerization methods (Docker, Singularity, Podman), container building and deployment;
• Knowledge of open source Cloud Computing platforms (OpenStack) and instances creation, management and deployment; 
• Experience with Cloud orchestration tools to automate deployment, scaling and management of containers (Kubernetes, OpenShift);
• Familiarity with Data Lakes technologies for Data Analytics and related Cloud Services (e.g. Hadoop, Spark).

In this research area, Leonardo is looking for researchers who have gained scientific work experience in one or more of the following domains: 

1. Advanced electromechanical systems for optical applications
2. Study and design of Metalenses for electro-optical systems
3. Neuromorphic electro-optical vision

Requirements for participation in the selection process

• Metalens technologies and design
• Electro-optical systems
• Modelling and simulation
• Scientific simulation using specific software (e.g. Matlab®, Phyton)
• Assessment and validation techniques
• Knowledge and design of systems based on neuromorphic vision sensors
• Vision sensors 
• Knowledge of algorithms for processing images and extracting information from images and video
• Artificial Intelligence and deep learning techniques applied to machine vision
• Design of ultra-rapid miniaturised electro-mechanical control systems

In this research area, Leonardo is looking for researchers who have gained scientific work experience in one or more of the following domains: 

1. Threat detection: Identifying complex attack patterns to improve detection, triage and attribution capabilities automatically suggesting the most effective defence strategies by improving the speed and effectiveness of cyber incident response processes.
2. Cryptography: Study of innovative solutions in  data protection domain broken down as data security  (protection against theft/unauthorised access) and data resilience against events that can lead to loss or corruption (data vaulting). Implementation and verification of cryptographic protocols on systems that use encryption to address real-world security concerns.
3. Active cyber defence: exploring methods, models, and use cases for building autonomous agents to be used in active defence activities also in a simulated environment.

Requirements for participation in the selection process

• Good cyber security knowledge
• Excellent knowledge of Python programming
• Excellent knowledge of machine learning and data science frameworks: scikit-learn, pandas, seaborn, xgboost, lightgbm, catboost, pytorch/tensorflow/keras
• Good knowledge of algorithms and graph theory
• Good knowledge of Generative Adversarial Networks (GAN)
• Good knowledge of Deep Learning techniques based on Recurrent Neural Networks, Transformers and Decision Trees
• Excellent knowledge of time-series analysis forecasting techniques
• Excellent knowledge of written and spoken English
• Good knowledge of GIT versioning software

In this research area, Leonardo is looking for researchers who have gained scientific work experience in one or more of the following domains: 

1. General Purpose Deep Learning: applied to one or more of the following areas, Self-Supervised Learning, Domain Adaptation, Few-shot Learning, Continuous Learning, Reinforcement Learning, Generative Deep Learning 
2. Trustworthy AI: for Explainable AI, Model Robustness, Dataset Analysis, Certified AI
3. Natural Language Processing: per svolgere task di Sentiment Analysis, Named Entity Recognition, Relation Extraction, Text Similarity, Text Summarization, Knowledge Graphs Construction
4. Computer Vision: deep learning techniques for Image Recognition, Super Resolution, Object Detection, Hyperspectral Image Analysis, Satellite Image Analysis, 
5. Audio and Signal Analysis: Audio Analysis, AI applied to Radar Technologies, Time series Analysis 

Requirements for participation in the selection process

• Bachelor/Master degree: Computer Engineering, Automation Engineering, Aerospace Engineering, Electronic Engineering, Data Science, Physics, Mathematics, Statistics or similar subjects
• Preferably a Master's and/or PHD in Machine Learning / Deep Learning / Data Science
• Advanced knowledge of Deep Learning, including: Neural Networks (e.g. CNN), Transformers (e.g. ViT/LLM), Recurrent Neural Networks (e.g. LSTM/GRU)
• Advanced knowledge of Python and Pytorch
• Good knowledge of written and spoken English
• Good teamwork skills
• Ability to manage research projects independently