PhD position in "Contracts for Distributed ML-Intensive Systems" - 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 academic cosupervision/ cotutelle track (2 years at IMT Atlantique + 1 year at Vrije Universiteit Brussel, Brussels, Belgium + short industrial visits.
1.1. Domain and scientific/technical context

Machine-learning techniques, in particular deep-learning algorithms, are nowadays more and more deeply integrated with other software systems (and hardware systems). Furthermore, these systems are frequently distributed today as the underlying data cannot be centralized because of, for example, stringent data privacy/security constraints or performance considerations. Overall such systems are referred to as distributed ML-intensive software systems.

One corresponding domain in which such systems are crucial are Cyber-Physical Systems (CPS), i.e., distributed software systems that are grounded in the physical world through various sensors and actuators (smart cities, autonomous vehicles, and industrial robots, etc.). Machine Learning (ML) subsystems have been proposed for some of their core components (e.g., process control based on image recognition and language processing techniques). The correct and safe integration of these ML techniques into the corresponding hardware and software systems poses substantial scientific and engineering challenges, notably because these systems often span the continuum from the IoT domain via the Edge to the Cloud. Another domain is the healthcare domain where biomedical analyses or the optimization of medical processes often involve distributed data, notably sensitive patient data, and computing facilities that cannot be shared.

1.2. Scientific/technical challenges

Programming language support and tool support is needed to ensure that ML-intensive distributed software systems satisfy properties of correctness & safety, security & privacy, and performance (in the sense of time/space/processor usage in distributed systems but also in the sense of precision/recall/… for ML algorithms); and this potentially spanning the space from IoT resource-constrained devices, over servers at the Edge level to large-scale data centers in the Cloud.

Guaranteeing these properties is a fundamental problem of ML-intensive systems. ML algorithms are typically defined in terms of very general templates with no dedicated language support that could provide support for the verification and enforcement of properties. In addition, the interactions between these algorithms and other software systems in which they are embedded is only defined using ad hoc methods. In particular, there is almost no support for property guarantees in terms of software contracts for such systems, one of the principal methods that support the definition of properties and their enforcement for software in general ([AHMM23] presents one of the first notions of contracts for ML-intensive systems).

1.3. Considered methods, targeted results and impacts

The main goal of this PhD is the design, precise definition and efficient enforcement of software contracts [Meyer92, Nguyen17] for ML-intensive distributed systems. We are targeting a programmatic definition of contracts that mediate interactions between ML software components and more traditional components. These contracts should be naturally embeddable in frequently-used libraries for ML systems, distributed systems, and reactive systems. The PhD candidate is to develop corresponding support for programming, enforcement and monitoring of such contracts. As part of the PhD thesis, we will also apply such contracts, with partners from industry and the healthcare domain, to cyber-physical systems and multi-party biomedical analyses.

The property support we target has a potentially a large impact because the problem of safeguarding complex software systems that harness deep-learning algorithms. This constitutes one of the major problems in the field of artificial intelligence, notably as a major problem on the societal level. In essence, the project’s outcomes have the potential to contribute means to safeguard ML-intensive systems.

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

• IMT Atlantique: Prof. Mario Südholt  and Assoc. Prof. Remous-Aris Koutsiamanis , IMT Atlantique, Nantes, France

  The PhD student will stay 2 years at IMT Atlantique.

• International partner: Prof. Coen De Roover  and Prof. Wolfgang De Meuter , Vrije Universiteit Brussel, Brussels, Belgium

  The PhD student will stay 1 year at VUB.

• Industrial partner(s) for short-term visits have not yet been determined. However, cooperations with non-academic partners on similar topics will be harnessed: e.g., with Nantes university hospital for healthcare applications and Zensor SA in Brussels for distributed health monitoring of industrial assets.

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. Vrije Universiteit Brussel

The VUB is an 'Urban Engaged University': our university connects. We forge links between our people - students, staff and stakeholders -, society and the wider world. We have always been urban because of our location in Brussels, capital of Belgium and Europe. And we are engaged in accordance with our principles of radical humanism and open, critical thinking. Through excellent research and qualitative education on a human scale, the VUB wants to make an active and engaged contribution to a better society.

Are you as concerned as we are about better living conditions, equal rights, peace, freedom of speech, a better environment? Well, you are in luck: as VUBer you could not be better placed to have an impact on these issues, thanks to the knowledge you acquire in your studies or your expertise as a researcher. But also because there are dozens of projects at the VUB where you can contribute to a better world. Initiated by people like you, people the world needs. Welcome to The World Needs You.

Requirements

Research Field

Computer science

Education Level

Master Degree or equivalent

Skills/Qualifications

The topic straddles the domains of software engineering, machine learning as well as data privacy and security. The development of language and tool support for the proposed contracts also requires expertise in programming languages, libraries and corresponding programming and execution mechanisms. In conjunction with the targeted application domains, industrial automation and healthcare processes, the PhD thesis presents many opportunities for interdisciplinary research.

Languages

ENGLISH

Level

Excellent

Research Field

Communication sciences

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/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