PhD Position in ML in the MSCA Doctoral Network ASSESS - at University of Patras, Greece

PhD Vacancy for a Doctoral Candidate (DC5) in ML vibration-based algorithms for damage diagnosis of smart FRP structures in the MSCA Doctoral Network ASSESS - at University of Patras, Greece

Job description
We are seeking a highly motivated Doctoral Candidate to develop and assess machine learning (ML) data-driven, random-vibration-based methods for robust and population-wide structural health monitoring (SHM) of smart CFRP composite structures. This project will address challenges posed by uncertainty in materials, manufacturing, and varying Environmental and Operating Conditions (EOCs). The methods will be built on novel concepts such as Optimized Multiple Model Representations (OMMR) and Functional Pooling, using MIMO transmittance-type stochastic models and PZT sensing. This PhD is part of the ASSESS project, you can read more about this here.

Position Objectives/Responsibilities:

• Develop and implement ML algorithms for SHM of smart CFRP composites under varying EOCs.
• Enhance fault detection and diagnosis for delamination and Barely Visible Impact Damage (BVID), aiming for high diagnostic performance and low false alarm rates.
• Ensure robustness to uncertainty in materials, manufacturing processes, and operating conditions.
• Operate using a limited number of sensors, with minimal data records for training, and avoid the need for large-scale finite element models (FEMs).
• Assess methods through Monte Carlo simulations and validation experiments with smart sandwich composites, GFRP wind turbine blades, and CFRP aircraft wing panel sections.
• Contribute to the development of an automated diagnostic system for smart sandwich composites and vibration-based damage assessment methods.

Research Fields:

The research fields for this position span multiple disciplines with the primary focus to be on data-driven vibration-based Structural Health Monitoring (SHM) of composite structures based on machine learning and stochastic approaches for signals and systems analysis and innovative solutions for robust damage diagnosis under uncertainty.

Secondments:

Polytechnic University of Bari in Italy, TUD Dresden University of Technology in Germany, Delft University of Technology in Netherlands.

Key Responsibilities:

• Conduct research as outlined in the project’s objectives under the supervision of Prof. John Sakellariou .
• Engage in secondments as part of the project’s training activities with Polytechnic University of Bari in Italy, TUD Dresden University of Technology in Germany, Delft University of Technology in Netherlands.
• Contribute to academic publications, project reports, and other dissemination activities.
• Participate in structured training programs and network-wide events organized by the consortium.
• Collaborate with international partners and other Doctoral Candidates within the network.

Principal Supervisor:

John Sakellariou, Assoc. Professor (Main Supervisor), Spilios Fassois, Professor (Co-Supervisor), Roger Groves, Assoc. Professor (Co-Supervisor)

Requirements
Eligibility Criteria

• A Master's degree (or equivalent) in Mechanical Engineering, Aerospace Engineering, Aeronautics or related fields
• Not in possession of a doctoral degree at the date of the recruitment.
• Recruited applicants can be of any nationality and must undertake trans-national mobility (i.e., move from one country to another) when taking up the appointment. In particular, at the time of selection, the recruited applicant for this position must not have resided or carried out their main activity (work, studies, etc.) in Greece for more than 12 months in the 3 years immediately prior to their recruitment. You will be asked to enclose evidence to prove this. Short stays, such as holidays, are not taken into account.-

Required Skills:

• Composite Materials and Structures: Strong understanding of the behavior, manufacturing, and damage mechanisms of composite materials, such as CFRPs and GFRPs.
• Structural Dynamics: Very good knowledge of vibration analysis, wave propagation, and finite element modelling (FEM).
• Stochastic Signals and Systems: Very good in analyzing stochastic systems, time series data, and signal processing.
• Structural Health Monitoring (SHM): Experience with data-driven vibration-based SHM methods and structural identification techniques.
• Programming: Excellent skills in MATLAB and/or Python for data analysis, modeling, and simulation.
• Strong conceptual and analytical skills
• The ability to work both independently and as part of a team

Optional Skills:

• Machine Learning: Basic knowledge of ML methods, particularly those applicable to data-driven diagnostics and predictive modeling.
• Experimental Experience: Hands-on experience with experimental modal analysis, structural dynamics testing, and vibration-based SHM.
• Research and Publications: Prior involvement in research projects and authorship of scientific publications in relevant fields.
• Interdisciplinary Collaboration: Ability to work effectively in a multidisciplinary and international research environment.
• English Requirement: High level of proficiency in English (will be tested at interview).

Academic Host:
The successful candidate will be hosted at the University of Patras in Greece, specifically within the Department of Mechanical Engineering & Aeronautics and the Laboratory of Stochastic Mechanical Systems and Automation.

University of Patras (https://www.upatras.gr/)

Established in 1964, the University of Patras is a prominent public academic institution in Greece, renowned for its commitment to education, research, and innovation across various disciplines. The university offers a wide range of undergraduate, graduate, and doctoral programs, fostering a dynamic academic environment that promotes interdisciplinary collaboration and excellence.

Department of Mechanical Engineering & Aeronautics (https://www.mead.upatras.gr/)

Founded in 1972, the Department of Mechanical Engineering and Aeronautics at the University of Patras provides comprehensive undergraduate and postgraduate programs. The department emphasizes cutting-edge research and practical applications in mechanical engineering and aeronautics, preparing students for successful careers in academia, industry, and research institutions.

Lab of Stochastic Mechanical Systems and Automation (SMSA) (https://sites.google.com/g.upatras.gr/smsa-lab/home)

The Laboratory for Stochastic Mechanical Systems & Automation (SMSA) is an international leader in advanced, highly innovative methods for stochastic mechanical systems. The lab focuses on the analysis and design of mechanical systems under uncertainty, integrating stochastic methods with automation technologies to advance research in mechanical engineering.

Conditions of employment
Salary:

The successful candidate will receive a competitive and attractive academic remuneration package in accordance with MSCA regulations for doctoral candidates. The researcher will be employed under a contract that includes social security coverage and pension rights.

The financial package includes the following*:

• Monthly living allowance: €3,400/month, adjusted by applying the country correction coefficient for the country of recruitment (Greece). The coefficients are outlined in Table 1 of MSCA Work Programme 2023-24 version adopted on 6 December 2022 (European Commission Decision C(2022) 7550 (https://adaptmet.eu/wp-content/uploads/2024/10/FINAL-PUBLISHED_6Dec2022_-wp-2-msca-actions_horizon-2023-2024_en.pdf)
• Monthly mobility allowance: €600/month.
• Monthly family allowance (if applicable, depending on family situation): €660/month.
• The living allowance above represents the total EU contribution to the researcher’s salary costs. The estimated gross salary is approximately €2,774.40 per month (only considering the living allowance), inclusive of both employee and employer tax contributions. The net salary will be calculated by deducting these contributions and any other applicable national taxes (e.g., income tax) from the gross amount.

Other Benefits:

The doctoral candidate will also benefit from comprehensive training within the ASSESS network, including participation in at least six specialized Training Events organized by the MSCA-ASSESS network. Additional opportunities include secondments to partner laboratories, a range of advanced training courses (including transferable skills development), and active engagement in workshops and international conferences, providing a well-rounded and enriching research experience. Expected Start Date: Q2 2025

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Prof. John Sakellariou, via sakj@upatras.gr.

Application procedure
Are you interested in this vacancy? Please apply no later than 28 February 2025 via the application button and upload the following documents:

• Detailed CV, including information on the candidate’s proficiency in English
• Motivational letter (1 page), describing why the position fits the applicant
• Contact information of 2 references
• Copy of Master’s degree diploma
• Copies of any other relevant certifications listed within CV

Selection Criteria: Candidates will be evaluated based on their academic background, research experience, and alignment with the project’s objectives. The selection process will be open, transparent, merit-based, impartial, and equitable.

Interview: Shortlisted candidates will be invited for a structured interview with predefined questions and a scoring system.

You can address your application to Prof. John Sakellariou.

Project Description:

The Horizon Europe MARIE SKŁODOWSKA-CURIE ACTION Doctoral Network (DN) ASSESS (Automated online monitoring of Smart compoSitE StructureS - Grant Agreement Number 101168031) offers 12 exciting PhD positions to develop next-generation smart composites for strategic European industries such as aviation, space, and wind energy.

Composite materials with embedded sensors and nanomaterials hold the potential for real-time structural health monitoring. However, industrial adoption is hindered by challenges in sensor integration, automated data analysis, standardization, and operator training. ASSESS bridges the gap between research and industry by advancing the design, manufacturing, and testing of Fibre Reinforced Polymer (FRP) composites.

As part of a multidisciplinary consortium of 9 beneficiaries and 13 Associated Partners, you will engage in pioneering research on:

• Smart composites and cutting-edge sensing technologies
• Advanced simulations and AI-driven data analysis
• Digital twins and Industry 4.0 innovations

Through collaborative projects, international secondments, and specialized training, you'll contribute to safer, lighter, and more efficient composite components, reducing CO₂ emissions, enhancing wind energy production, and supporting Europe's green transition.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.

40 hours per week

Mekelweg 5