Ph.D. position at the Politecnico di Torino (PoliTo, Italy) for the IN-DEEP European Doctoral Network: Real-time inversion using self-explainable Deep Learning driven by expert knowledge

  • Torino
  • 3.170 € al mese
  • Tempo determinato
  • Full time
  • 1 mese fa
Offer DescriptionAdaptive strategies for explainable Deep PDE solvers to speed up the generation of large and significant datasets.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 visitExpected 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 publications2+ participation in relevant international conferencesRequirementsResearch Field Mathematics » Applied mathematics Education Level Master Degree or equivalentResearch Field Physics » Computational physics Education Level Master Degree or equivalentResearch Field Engineering » Simulation engineering Education Level Master Degree or equivalentResearch Field Computer science » Modelling tools Education Level Master Degree or equivalentSkills/QualificationsFamiliar with Python and/or C++ languagesFamiliar with neural networks and deep learning algorithmsExperience with numerical methods for partial differential equationsAble to work independently and flexibly, taking initiative where requiredAble to communicate and collaborate effectively in a team settingSpecific RequirementsM.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 degreeOfficial Transcript of RecordsSyllabus/Course DescriptionMaster's degree OR official university document stating provisional date of graduation (if not graduated yet)Official Transcript of RecordsSyllabus/Course DescriptionThe 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:Be exempted from presenting an English language certificate in accordance with the terms of Annex 4 of the Call for Admission.Languages ENGLISH Level GoodResearch Field Mathematics » Computational mathematicsComputer science » ProgrammingAdditional InformationBenefitsSalary: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.Eligibility criteriaMobility: 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.Selection processEvaluation criteria:Step 1:Academic performance during the undergraduate studies - 20 pointsResearch experience in the area of the call, including publications, projects, and internships - 20 pointsAwards, honours, other significant roles and achievements as a student - 10 pointsAdditional coursework, certifications, training programs, continuous learning - 5 pointsMotivation letter 5 pointsA short proposal (maximum 2 pages) of an individual project on the use of Neural Networks to solve partial differential equations 10 pointsStep 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 pointsRecommendation letters 5 pointsAdditional commentsThe candidate must submit a motivation letter, the individual project and a CV structured into the following sections:Academic performance during the undergraduate studiesResearch experience in the area of the call, including publications, projects, and internshipsAwards, honours, other significant roles and achievements as a studentAdditional coursework, certifications, training programs, continuous learningFor further information please contact: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 GeofieldWhere to apply E-mailstefano.berrone@polito.itContact State/ProvinceTO CityTorino WebsiteStreetCorso Duca degli Abruzzi Postal Code10129 E-Mailstefano.berrone@polito.itsandra.pieraccini@polito.itSTATUS: EXPIRED

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