Ph.D.s, Post-Docs and Internships
The HiCrest research group is always searching for talented candidates looking to pursue fully-funded Ph.D. positions both in Computer and Industrial Engineering. Furthermore, postdoctoral or internship positions may be provided to motivated candidates, depending on available resources.
To express your interest, please contact us at hicrest@unitn.it. Be sure to prepend “[JOB@HICREST] ” at the beginning of the subject line, followed by your name. When sending such an application, it is mandatory to include a full curriculum vitae, complete with the information regarding your academic and professional career.
Current HiCrest members are generally characterised by a strong background in computer science, parallel computing, mathematics and general purpose computing systems. Given the interdepartmental nature of the research topics covered by HiCrest, it is expected that candidates are able to study and work independently.
Applicants must be proficient with written and spoken English at an academically compliant level.
Open Positions
The High-Performance Computing and Reliable Systems Laboratory (HiCREST) at the Università di Trento is periodically seeking outstanding candidates who are interested in pursuing a PhD degree in the area of Parallel Computing and Reliable Systems:
Parallel Computing
We are particularly interested in candidates who are passionate about designing and implementing the next generation of parallel computing systems and algorithms. The successful candidate will have the opportunity to conduct research in the following areas:
- Parallel algorithms for Graph Analytics and Graph-Based learning models.
- Programming models and algorithms for emerging power-efficient architectures.
- Applied Mathematics and Sparse Linear Algebra on GPU.
- Simulation of Quantum Systems and hybrid programming models.
- Emerging programming paradigms (in-network computing, processing in-memory).
- Post Moore accelerators.
Reliable Systems
The interaction between computing systems and the surrounding environment requires to guarantee a fault-free computation. We are seeking new efficient solutions to make advanced computing systems trustworthy. The successful candidate will have the opportunity to face this challenge, pursuing research in the following topics:
- Reliable autonomous vehicles, from self-driving cars to space exploration.
- Trustworthily machine learning models.
- Increasing the robustness of quantum circuits computation.
- Novel architectures and technologies reliability evaluation and improvement.
Please submit your Expression of Interest by the 1st of June 2026 by sending your CV and 1 page of your research statement. Successful applicants will be invited to submit formal applications in due course.
Mandatory Requirements
- A Master’s Degree (or equivalent) in computer science, information engineering, or equivalent topics; Master students who expect to obtain their degrees by 31 October 2026 can also apply.
- English level certification (TOEFL or others).
Ph.D. Salary and Starting Date
- Duration: a Ph.D. in Italy takes 3 years.
- Salary: the scholarship is approximately 1600 €/month after tax plus extra salary during the abroad period and abroad visits or internships. Teaching duties are not mandatory, and are paid as an extra compensation atop of the salary.
- Starting date: the starting date of the Ph.D. scholarship is 01/11/2026.
To get more information, visit the following links:
- Information on becoming a Ph.D. student in UNITN.
- Information on doctoral scholarships.
The University of Trento and the Hicrest Laboratory invite applications for one (1) PhD student position on efficient and reliable inference in modern AI systems.
The project will investigate techniques such as quantization, sparsification, and pruning to reduce the computational cost, memory footprint, and energy consumption of deep learning models, while carefully assessing their impact on accuracy, runtime performance, and reliability.
The successful candidate will develop tools, benchmarks, and optimization methods for characterising and improving
inference workloads across models, datasets, hardware platforms, and deployment conditions.
The work will contribute to the ARCHYTAS project’s framework and will target reproducible, experimentally grounded research in AI systems.
Candidate profile
We are looking for a motivated candidate with a strong background in computer science, computer engineering, machine learning systems, or a related field.
Required qualifications
- Master’s degree, or equivalent, in Computer Science, Computer Engineering, Electrical Engineering, Data Science, Artificial Intelligence, or a related discipline;
- Strong programming skills, preferably in Python and/or C/C++;
- Familiarity with deep learning frameworks such as PyTorch, TensorFlow, ONNX Runtime, or similar;
- Interest in systems-oriented AI research, benchmarking, performance analysis, and reproducible experimentation;
- Good written and spoken English.
Desirable qualifications
Experience in one or more of the following areas will be considered an advantage:
- Deep learning inference optimization; quantization, pruning, sparsity, or model compression;
- GPU programming, CUDA, or accelerator-based computing;
- Performance profiling and benchmarking; reliability analysis, fault tolerance, or approximate computing;
- Energy-efficient computing;
- High-performance computing or heterogeneous systems.
What we offer
The selected candidate will join an active research environment at the University of Trento and will work on a timely topic at the intersection of AI, systems, and efficient computing.
The position offers:
- A fully funded 3-year PhD position (1.6K euros per month after tax);
- Opportunities to publish in international conferences and journals;
- Access to experimental infrastructure for AI and systems research;
- Collaboration opportunities within the Archytas framework and related research initiatives; support for attending conferences, workshops, summer schools, and research visits, subject to project rules and available funding;
- Internship at Covision Lab.
To express your interest, please send an email with your CV and a 1-page research and motivation statement highlighting how your skills and achievements match the qualifications required. The deadline is set for the 31st of July 2026.
Check our LinkedIn page for any further updates!