Engineer F/M - Scientific programmer in federate learning with applications in neuroscience

Engineer F/M - Scientific programmer in federate learning with applications in neuroscience Download job offer in PDF format Contract type : Fixed-term contract Level of qualifications required : Graduate degree or equivalent Fonction : Temporary scientific engineer Level of experience : From 3 to 5 years About the research centre or Inria department Created in 2008, the Inria center at the University of Lille employs 360 people, including 305 scientists in 16 research teams. Recognized for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria center at the University of Lille maintains a close relationship with large companies and SMEs. By fostering synergies between researchers and industry, Inria contributes to the transfer of skills and expertise in the field of digital technologies, and provides access to the best of European and international research for the benefit of innovation and businesses, particularly in the region. For over 10 years, the Inria center at the University of Lille has been at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT). Context The person will join the cross disciplinary project Loop (closed Loop neurOtechnologies: from sensOrs to aPplications). The project will implement an interdisciplinary strategy applied to the development of a mechanism-based therapy for drug-resistant hallucinations in patients with schizophrenia. The project will be structured around three main research pillars: 1) the algorithmic level of closed-loop systems (online signal processing, machine learning); 2) the design of a complete and non-invasive solution to address the question of refractory hallucinations, and study how closed-loop interaction schemes can be beneficial for highly impaired psychiatric patients; 3) the design of the sensors themselves and translational research with animal models, in order to enhance the quality of the recordings and pave the way for future invasive miniaturized solutions. In this context, the objective is to apply federated and decentralized learning techniques to learn predictive models. Assignment The objective is to adapt the declearn API to the specific case of FRMI and EEG data, time series and eventually to address the problem of federated learning in the neuromorphic paradigm. The work plan is the following • Join the team that writes the data preparation pipeline. The challenges are the scalability with respect to data size, data dimensionality, and time dependent data. The declearn readers and data representation choices will be monitored and adapted to the new choices and constraints. • Adapt and implement federated algorithms tailored to the learning problem specifications. A specific attention will be on the scalability and the efficiency of the communications. • Extend DecLearn to the fully decentralized setting. • Address the problem of privacy. • Implement specific approaches for neuromorphic computation. Main activities • Develop code. • Write documentation. • Write tests. • Launch experiments. • Report activity in the consortium. Skills Technical skills and level required : • a strong understanding of distributed algorithms • software design and development skills (relevant code may include Python and Rust) Languages : • Mastering English is essential Relational skills : • smoothly working in a team in a reseach environment • effective communication and collaboration • eager to learn in an academic setting Benefits package • Subsidized meals • Partial reimbursement of public transport costs • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) • Possibility of teleworking and flexible organization of working hours • Professional equipment available (videoconferencing, loan of computer equipment, etc.) • Social, cultural and sports events and activities • Access to vocational training • Social security coverage Apply for this position Share • Facebook • Linkedin • Twitter • Email General Information • Theme/Domain : Data and Knowledge Representation and Processing Statistics (Big data) (BAP E) • Town/city : Villeneuve d'Ascq • Inria Center : Centre Inria de l'Université de Lille • Starting date : 2027-03-01 • Duration of contract : 2 years • Deadline to apply : 2026-11-18 Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed. Instruction to apply Defence Security : This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment. Recruitment Policy : As part of its diversity policy, all Inria positions are accessible to people with disabilities. Contacts • Inria Team : MAGNET • Recruiter : Tommasi Marc / Marc.Tommasi@inria.fr About Inria Inria, the French national institute for research in digital science and technology, supports the French government in national research and innovation strategies in the digital field, acting as Digital Programs Agency. Inria leads over 300 research and innovation projects with its 3,500 scientists, engineers, and support staff, in partnership with universities and the digital ecosystem (businesses, entrepreneurs, and public stakeholders). Together, we explore strategic fields such as artificial intelligence, cybersecurity, quantum computing, cloud technologies, digital transformation in healthcare, digital twins, and digital technologies for defence. We develop practical solutions such as software, tech startups, partnerships with national companies, and cutting-edge training programmes. Our goal is to drive scientific, technological, and industrial excellence to ensure France’s digital sovereignty.