University of Naples Federico II
PHD POSITIONS IN “TUAI PROJECT” - Towards an Understanding of Artificial Intelligence via a tra[]
Job Location
it, Italy
Job Description
Mathematics and Applications "R. Caccioppoli" Organisation/Company: University of Naples Federico II Department Mathematics and Applications "R. Caccioppoli" Research Field: Computer science » Digital systems Researcher Profile: First Stage Researcher (R1) Positions: PhD Positions Country: Italy Application Deadline: 28 Feb 2025 - 12:00 (UTC) Type of Contract: Temporary Job Status: Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? Yes Offer Description The TUAI project aims to foster a new generation of researchers with a comprehensive understanding of Artificial Intelligence (AI) by promoting a transparent, open, and explainable perspective. The selected Early Stage Researchers (ESRs) will work on innovative research topics that bridge the gap between technical AI advancements and societal needs, ensuring that AI systems are designed and deployed ethically, responsibly, and inclusively. Successful candidates will be involved in the following activities: Conduct research within the scope of transparent and explainable AI, with a particular focus on federated learning, graph neural networks, generative approaches, and others to enhance the interpretability and usability of AI systems. Collaborate with a multidisciplinary team of researchers and industry experts across Europe. Participate in research training courses, workshops, and summer schools to further develop skills and expertise. Contribute to the dissemination and communication of research findings within academic and non-academic settings, including presenting at top-tier conferences. Where to apply E-mail: modal.unina.hiringgmail.com Requirements Research Field: Computer science Education Level: Master Degree or equivalent Skills/Qualifications: Demonstrated deep scientific and technical knowledge, evidenced by publications or successful projects, in one or more of the following areas: Machine learning and neural network architectures (e.g., convolutional, recurrent, and transformer networks) Generative AI Federated Learning Graph Neural Network Large Language Models Scientific Machine Learning Big data technologies and tools, with the capability to work with large datasets to derive predictive analytics and insights Familiarity with the latest AI trends and developments, and the ability to apply these advances to practical, real-world challenges Proficiency in Python is mandatory. Knowledge of additional programming languages such as C++, R, or Rust is considered a plus. Proficiency in using key Machine Learning and Deep Learning frameworks, particularly TensorFlow and PyTorch, is required. Familiarity with Visual Studio and its integration with relevant programming languages. Strong knowledge of Linux systems. Experience using version control systems such as Git, GitHub, GitLab, or similar tools for collaborative software development and version management. An excellent academic record and proficiency in English (both written and spoken) at a minimum B2 level according to the European Framework of Reference. Proficiency will be assessed during the interview, and proof of language competency (e.g., certificate) may be required. Specific Requirements: Must not have resided or carried out their main activity (work, studies, etc.) in the country of the host institution for more than 12 months in the 3 years immediately prior to the recruitment date. Must hold a Master’s degree in a relevant field (e.g., Artificial Intelligence, Computer Science, Data Science, Mathematics, Engineering, or related disciplines) by the start date of the position. Applicants who have already completed a PhD are not eligible. Languages: ENGLISH Level Excellent Research Field: Computer science » Digital systems, Engineering » Computer engineering Years of Research Experience: 1 - 4 The successful candidate will receive an attractive salary (around 3.3K) in accordance with the MSCA regulations for Early-Stage Researchers. The exact (net) salary will be confirmed upon appointment and is dependent on local tax regulations and on the country correction factor (to allow for the difference in cost of living in different EU Member States). In addition to the base salary, there are additional allowances provided, such as a living allowance, a mobility allowance, and a family allowance (if applicable), which further increase the total compensation package. Furthermore, TUAI will offer to take advantage of joint scientific research trainings, transferable skills workshops, and international conferences. For more information about the project and consortium contact us (email below). Additional Benefits: International Research Environment: Join the dynamic and vibrant M.O.D.A.L. lab (https://www.labdma.unina.it), an international research hub that fosters collaboration across academic and industry sectors, providing an enriching environment for professional and personal growth. Mobility and Collaboration: Experience mobility across prestigious partner institutions and industry partners in multiple countries, gaining exposure to diverse research methodologies and collaborative projects. Living in Naples: Enjoy living in the enchanting city of Naples, renowned for its rich history, cultural heritage, gastronomy, and vibrant lifestyle, all while benefiting from a comparatively affordable cost of living. Naples is a vibrant and bustling city located on the southwest coast, nestled in a stunning gulf and surrounded by renowned tourist and archaeological sites such as Capri, Ischia, the Amalfi Coast, Pompeii, Herculaneum, and Mount Vesuvius. For more information, visit https://www.visitnaples.eu/en. Selection process How to Apply: Interested candidates should submit the following documents to modal.unina.hiringgmail.com with the email subject: "TUAI - Name Surname" (e.g., "TUAI - John Doe"): A detailed and updated scientific CV, including your contact information, and highlighting educational qualifications (e.g., Laurea degrees), relevant professional experience (e.g., internships), programming languages known, and tools or technologies used. Please highlight starting availability. The CV should be saved as name_surname.pdf (e.g., john_doe.pdf). A motivation letter (maximum 2 pages) highlighting your experience and alignment with the ESR position. Alternatively, you may provide a video motivation (maximum 2 minutes). While the video format is preferred, it is not mandatory. However, the written motivation letter is compulsory. If submitting a video, please include a link to the video rather than attaching it directly to the email. Name and contact details of at least one referee who would be willing to write a letter of support for your application or be contacted. Copies of your degree certificates and academic transcripts. In case, MSc is to be completed before the starting of this position, please provide expected final grade and completion date and availability. List of publications and patents (if applicable). Any English language and other relevant certificates (if applicable). MANDATORY APPLICATION FORM: Complete the application form available at https://forms.gle/4UapoajGZ5Mezruk7. Submission of this form is compulsory. Applicants who complete steps 1-6 but do not fill out the form will not be considered for the position. Please ensure that all information provided in the form is truthful, as it will be thoroughly reviewed and verified during the interview process Selection Process The selection process will consist of the following stages: Initial Screening: Candidates whose profiles are deemed a good fit based on CV screening and evaluation of their motivation letter or video will be invited to a two-stage interview process. Two-Step Interview Process: First Interview: This will be an introductory and technical/theoretical interview aimed at assessing the candidate's knowledge in the relevant research areas and evaluating their proficiency in English. Final Technical Interview: Candidates who successfully pass the first stage will proceed to a more in-depth technical interview. During this session, candidates will be asked to complete real-time programming tasks or similar practical exercises to demonstrate their coding skills and problem-solving abilities. This stage will assess hands-on expertise in programming languages, machine learning frameworks, and the ability to solve complex technical challenges under timed conditions, including tasks such as connecting to remote servers, using version control systems like Git, and troubleshooting technical issues. There will be a series of interview rounds held approximately twice a month. Successful candidates will be included in the nearest round upon receipt and evaluation of their application. J-18808-Ljbffr
Location: it, IT
Posted Date: 11/28/2024
Location: it, IT
Posted Date: 11/28/2024
Contact Information
Contact | Human Resources University of Naples Federico II |
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