PhD position in "A transformation language for simultaneous data integration and inference in digital twins" - MSCA Cofund SEED programme

2 Feb 2024
Job Information

Organisation/Company

IMT Atlantique

Department

Doctoral division

Research Field

Computer science » Programming

Researcher Profile

First Stage Researcher (R1)

Country

France

Application Deadline

14 Feb 2024 - 12:00 (Europe/Paris)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

37

Offer Starting Date

1 Sep 2024

Is the job funded through the EU Research Framework Programme?

HE / MSCA COFUND

Marie Curie Grant Agreement Number

101126644

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description
The PhD position is offered under an academic cosupervision/ cotutelle track (2 years at IMT Atlantique + 1 year at Luxembourg Institute of Science and Technology, Luxemburg City  + short industrial visits
1.1. Domain and scientific/technical context

Digital Twins (DTs) integrate in real time heterogeneous data sources, coming from sensors, devices, and subsystems of the physical counterpart. This integration is especially important in large-scale DTs, from the domain of manufacturing systems up to nation-wide DTs. However, not all data needed by DTs is directly measurable in the physical system, e.g. because of the costs of the corresponding sensors. Hence, besides integrating observed data, DTs need also to infer non-observed data. Given the heterogeneity of the possible data sources, and the difficulty in inferring meaningful data, these phases are generally very costly.

1.2. Scientific/technical challenges

In the state of the art, data integration and data inference for DTs are performed in separate steps by different tools. Model Transformation (MT) languages have a natural application in the data integration step. Machine Learning (ML) techniques are instead prominently used for data inference, after training on historical traces of the system or simulations. Executing these two steps sequentially has however important drawbacks: 1) if inference is performed before integration, then it may effectively infer only local data about a device or subsystem; 2) if integration is performed before inference, then the information loss during integration may negatively impact the inference potential.

1.3. Considered methods, targeted results and impacts

We argue that data integration and inference for DTs should be defined and performed at the same time. However, defining the integration+inference logic as a single step is not trivial, since it involves two different sets of competences. We aim at a linguistic solution to this problem, by designing and implementing a single language for the simultaneous specification of integration and inference of sensor data into the DT model. The language will be obtained by extending a MT language with ML capabilities. Users will be able to define transformation rules for data integration, coupled with ML tasks that are aware of the integration logic, avoiding both information loss and restriction to local views. This would allow DT engineers to reduce the costs of the data integration and inference phase. This will also increase the applicability of the partners’ tools in DTs of several domains.

2. Partners and study periods
2.1. Supervisors and study periods

• IMT Atlantique: Assoc. Prof. Massimo Tisi , IMT Atlantique, Nantes, France

  The PhD student will stay 2 years at Prof. Tisi's lab.

• International partner: Dr. Jean-Sébastien Sottet , research engineer, Luxembourg Institute of Science and Technology, Luxemburg City, Luxemburg

  The PhD student will stay 1 years at Dr. Scottet's lab.

• Industrial partner(s):

2.2. Hosting organizations
2.2.1. IMT Atlantique

IMT Atlantique , internationally recognized for the quality of its research, is a leading French technological university under the supervision of the Ministry of Industry and Digital Technology. IMT Atlantique maintains privileged relationships with major national and international industrial partners, as well as with a dense network of SMEs, start-ups, and innovation networks. With 290 permanent staff, 2,200 students, including 300 doctoral students, IMT Atlantique produces 1,000 publications each year and raises 18€ million in research funds.

2.2.2. Luxembourg Institute of Science and Technology

LIST  brings together diverse and complementary skills in information and communication technologies, environmental technologies, biotechnologies and advanced materials. This unique grouping makes it possible to create synergies essential for building a reinvented economy and society. In this way, LIST enables adopting of a holistic approach to complex problems such as rejuvenating industry, modernising mobility, digitalising the economy, the sustainable management of energy and natural resources, and space technologies. Our aim: to be a catalyst for high-impact innovation.

Requirements

Research Field

Computer science

Education Level

Master Degree or equivalent

Skills/Qualifications

While the proposed topic is strongly rooted in software language engineering, it will be applied to a Luxembourg-wide DT focused on public transport, and addressing the environmental and energetic transition.

Languages

ENGLISH

Level

Excellent

Research Field

Computer science

Additional Information
Benefits
A PhD programme of high quality training : 4 reasons to apply

• SEED is a programme of excellence that is aware of its responsibilities: to provide a programme of high quality training to develop conscientious researchers, including training in responsible research and ethics. 
• SEED’s unique approach of providing interdisciplinary, international and cross-sector experience is tailored to work in a career-focused manner to enhance employability and market integration.
• SEED offers a competitive funding scheme, aiming for an average monthly salary of EUR 2,000 net per ESR, topped by additional mobility allowances as well as optional family allowances.
• SEED is a forward-looking programme that actively engages with current issues and challenges, providing research opportunities addressing industrial and academic relevant themes.

Eligibility criteria

Eligibility criteria. In accordance with MSCA rules, SEED will open to applicants without any conditions of nationality nor age criteria. SEED applies the MSCA mobility standards and necessary background. Eligible candidates must fulfil the following criteria

• Mobility rule: Candidates must show transnational mobility by having not resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the three years immediately before the deadline of the co-funded program's call (Jan 31, 2024 for Call#1). Compulsory national service, short stays such as holidays and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not taken into account.
• Early-stage researchers (ESR): Candidates must have a master’s degree or an equivalent diploma at the time of their enrolment and must be in the first four years (full-time equivalent research experience) of their research career. Moreover, they must not have been awarded a doctoral degree.
  Extensions may be granted (under certain conditions) for maternity leave, paternity leave, as well as long-term illness or national service.

Selection process

The selection process is described on the guide for applicants available here: https://www.imt-atlantique.fr/en/research-innovation/phd/seed/documents

Additional comments

Applications can only be provided through the application system available under the SEED website: https://www.imt-atlantique.fr/en/research-innovation/phd/seed

Website for additional job details

https://www.imt-atlantique.fr/en/research-innovation/phd/seed

Work Location(s)

Number of offers available

1

Company/Institute

IMT Atlantique

Country

France

City

Nantes

Postal Code

44307

Street

4, rue Alfred Kastler - La Chantrerie

Geofield

Where to apply

Website

https://www.imt-atlantique.fr/en/research-innovation/phd/seed

Contact

City

Nantes

Website

https://www.imt-atlantique.fr/en/research-innovation/phd/seed

Street

4, rue Alfred Kastler - La Chantrerie

Postal Code

44307

E-Mail

[email protected]

STATUS: EXPIRED