- JOB
- Italy
Job Information
- Organisation/Company
- Politecnico di Torino
- Department
- Dipartimenti di Scienze Matematiche "G.L. Lagrange"
- Research Field
- Mathematics » Computational mathematicsEngineering » Simulation engineering
- Researcher Profile
- First Stage Researcher (R1)
- Positions
- PhD Positions
- Country
- Italy
- Application Deadline
- Type of Contract
- Temporary
- Job Status
- Full-time
- Offer Starting Date
- Is the job funded through the EU Research Framework Programme?
- Horizon Europe - MSCA
- Reference Number
- DC5
- Marie Curie Grant Agreement Number
- 101119556
- Is the Job related to staff position within a Research Infrastructure?
- No
Offer Description
Adaptive strategies for explainable Deep PDE solvers to speed up the generation of large and significant datasets.
The work will focus on the development of new numerical methods for solving PDEs based on Machine Learning strategies.
The activity will be organized according to the following scientific tasks:
- Design and implement a novel variational physics-informed neural network with optimal trial and test spaces.
- Study the stability, approximation properties, and convergence of the novel method.
- Generate a large and significant database for training a DNN on a benchmark problem in geophysics.
For more information on the IN-DEEP Doctoral Network, please visit https://www.in-deep.science
Expected outcomes:
- A novel variational physics-informed neural network with optimal trial and test spaces.
- Theoretical analysis of the method and numerical validation.
- Fast massive database simulation to train a DNN for an inverse problem in geophysics.
- 2+ peer-reviewed publications
- 2+ participation in relevant international conferences
Where to apply
- stefano.berrone@polito.it
Requirements
- Research Field
- Mathematics » Applied mathematics
- Education Level
- Master Degree or equivalent
- Research Field
- Engineering » Simulation engineering
- Education Level
- Master Degree or equivalent
- Research Field
- Physics » Computational physics
- Education Level
- Master Degree or equivalent
- Research Field
- Computer science » Modelling tools
- Education Level
- Master Degree or equivalent
- Experience with Numerical Methods for Partial Differential Equations
- Familiar with Computational Linear Algebra
- Familiar with Python and/or C++ languages
- Familiar with neural networks and deep learning algorithms
- Able to work independently and flexibly, taking initiative where required
- Able to communicate and collaborate effectively in a team setting
- M.Sc. degree (i.e. 2° level title, as defined by the Bologna Process), issued by an officially recognized academic institution, which grants admission in PhD programmes in the country of issuance. To evaluate the University career, the candidate should provide:
Bachelor's degree
Official Transcript of Records
Syllabus/Course Description
Master's degree OR official university document stating provisional date of graduation (if not graduated yet)
Official Transcript of Records
Syllabus/Course Description
- The documents shall be issued by the relevant university.
- Documents issued in Italian, English, French, and Spanish are accepted. If the documents are written in other languages, please upload together both the original version AND the official translation in Italian or English and attach the merged document.
- Academic qualifications are accepted to take part in the selection process with the minimum average grade illustrated in Annex 3 of the Call for Admission.
- The original diplomas and transcripts should be available by 31st October at the latest (or before enrollment to PoliTo).
- One of the following certificates of English language knowledge, regardless of the date of obtainment:
- IELTS: minimum score 5.5;
- one of the language certificates accepted in substitution for IELTS 5.5 by Politecnico di Torino and listed in the table “Table of 23/09/2019 updated on 22/12/2022 (transitional period)” available at: https://didattica.polito.it/zxd/b5eda0a74558a342cf659187f06f746f/9dde3c1deee7c791026d6a0ac91322bb/f318d418925e3b3fe050c0828c37718b?1674658551728
- Be exempted from presenting an English language certificate in accordance with the terms of Annex 3 of the Call for Admission.
- Languages
- ENGLISH
- Level
- Good
- Research Field
- Mathematics » Computational mathematicsEngineering » Communication engineering
Additional Information
Salary:
The gross monthly salary is approximately €3,170 (38.040 per year), leading to an estimated net income of €2800 per month (33.600 per year), which encompasses a mobility allowance of €600. Additionally, eligible individuals may receive a family allowance of €660 per month along with a special needs allowance.
- Mobility: at the time of recruitment, the researcher must not have resided or carried out his/her main activity (work, studies, etc.) in Italy for more than 12 months in the 36 months immediately before the recruitment date. Time spent as part of a procedure for obtaining refugee status under the Geneva Convention or compulsory national service is not considered.
- The candidate must be at the date of recruitment a doctoral candidate (i.e. not already in possession of a doctoral degree). Researchers who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will not be considered eligible.
- The candidate must agree to work exclusively for the action.
- Step 1:
- Academic performance during the undergraduate studies - 20 points
- Research experience in the area of the call, including publications, projects, and internships - 20 points
- Awards, honours, other significant roles and achievements as a student - 10 points
- Additional coursework, certifications, training programs, continuous learning - 5 points
- Motivation letter 5 points
- A short proposal (maximum 2 pages) of an individual project on the use of Neural Networks to solve partial differential equations 10 points
- Step 2: Only for those scoring 40 or above in step 1:
- Interview to assess communication skills, initiative, critical thinking, and motivation to pursue a PhD on the topic of the call. - 25 points
- Recommendation letters 5 points
Additional comments
The candidate must submit a motivation letter, the individual project and a CV structured into the following sections:
- Academic performance during the undergraduate studies
- Research experience in the area of the call, including publications, projects, and internships
- Awards, honours, other significant roles and achievements as a student
- Additional coursework, certifications, training programs, continuous learning
For further information please contact: stefano.berrone@polito.it and sandra.pieraccini@polito.it
Women are encouraged to apply!
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- Politecnico di Torino
- Country
- Italy
- State/Province
- Torino
- City
- Torino
- Postal Code
- 10129
- Street
- Corso duca degli Abruzzi, 24
- Geofield
Contact
- State/Province
- Torino
- City
- Torino
- Website
- Street
- Corso Duca degli Abruzzi
- Postal Code
- 10129
- stefano.berrone@polito.itsandra.pieraccini@polito.it