Postdoctoral position “Newtonian noise cancellation through machine learning: bridging the gap between geophysics and gravitational Waves”

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Postdoctoral position “Newtonian noise cancellation through machine learning: bridging the gap between geophysics and gravitational Waves”

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Offer DescriptionSTART DATE: BETWEEN 1ST NOV. 2024 AND 1ST JAN. 2025Liège is one of the most multicultural and dynamic cities in the heart of Europe, less than an hour from Brussels and Cologne, two hours from the seacoast, two hours from Paris, and three hours from London or Amsterdam by train. The city hosts the largest European urban music festival, les Ardentes, many mythic sport events such as Liège-Bastogne-Liège or the F1 Grand Prix of Francorchamps, and hosts the Royal Opera of Wallonia.The University of Liège was founded in 1817 is the largest French-speaking university in Belgium. It has more than 5,700 staff members across four campuses, and around 27,000 students of 123 different nationalities. We welcome applicants with diverse backgrounds and experiences and support gender equality and diversity which we consider as a strength and an asset. Since 2011, ULiège has been proud to display the European (HRS4R) label, which reflects its commitment to open, transparent and merit-based procedures.The faculties of Sciences and the Engineering School have a longstanding history in terms of collaborative research and are located nearby on the Campus of Sart-Tilman. Located on the hills of the Sart-Tilman in a green environment with sports facilities next to the University, the campus offers rapid access to the City center through bus, bike, or car. Housing can be found close to the Campus or in the City center. The work is hosted by three research laboratory: OGrav led by Prof. Maxime Fays, APGEO led by Prof. Frédéric Nguyen and PML led by Prof. Christophe Collette.The team specialising in Gravitational Wave Theory, or OGrav, is at the forefront of theoretical research in this domain. Their expertise in gravitational wave physics and machine learning is key to interpreting and mitigating the complex interactions of the Newtonian noise in the EMR region with the instrument output. This theoretical understanding is vital for laying the groundwork for practical experimentation and technological innovation.Complementing OGrav’s theoretical insights, the Precision Mechatronics Laboratory (PML) focuses on the practical aspects of gravitational wave detection. Their work, centred around examining the effects of Newtonian noise on detector prototypes, is critical in refining the technology for gravitational wave detection. Their efforts are essential in bringing theoretical models to life, ensuring that the detectors are both precise and sensitive.The third pillar of this collaboration involves the Applied Geophysics (APGEO) group, with a focus on the imaging of the EMR site within the Einstein Telescope collaboration. Their expertise in creating and utilizing geological models is instrumental in estimating Newtonian noise. This group’s work provides a crucial link between the theoretical predictions of OGrav and the practical applications developed by PML. Their understanding of the geological framework of the region adds a layer of empirical data that is invaluable for the overall project.SUBJECT DESCRIPTIONThe postdoctoral researcher will focus on machine-learning-based Newtonian Noise subtraction for the Einstein Telescope, including the development, implementation, and experimental tests of the method on the E-TEST prototype developed in Liège. Your task will be to model Newtonian noise by coupling existing models in elastodynamics (e.g. SALVUS) with gravity computation from the seismic acceleration to be able to cancel it from gravitational waves signals. A significant part of your work will involve demonstrating that a machine learning model, possibly a Convolutional Neural Network (CNN) or a Variational Autoencoder (VAE), can accurately predict a test mass motion caused by a controlled artificial noise (moving/vibrating mass).You will be working side by side with another researcher focused on the experimental set-up that you will model.JOB DESCRIPTIONWe are looking for a motivated researcher who can work with multiple research teams at Uliège.This person will be responsible for carrying out numerical computation of Newtonian noise, develop its subtraction for a controlled artificial noise and lay out the foundations for real-world developments which will include realistic geophysical profiles to account for the variations of the elastic parameters in space.YOUR PROFILERequired qualifications:

• MASTER’S DEGREE IN ENGINEERING or PHYSICS
• PhD DEGREE IN COMPUTATIONAL GEOPHYSICS, MACHINE LEARNING OR NEWTONIAN NOISE

Desirable skills:

• EXCELLENT WRITTEN AND VERBAL COMMUNICATION SKILLS IN ENGLISH
• COMPUTATIONAL (GEO)PHYSICS AND MACHINE LEARNING METHODS

Soft skills:

• TEAM SPIRIT
• AUTONOMOUS
• ORGANISATIONAL SKILLS
• FAST LEARNER

Note that the candidate must not have spent more than 24 months as a resident of Belgium over the last 3 years.EMPLOYMENT TERMS

• Type of contract : postodoctoral researcher
• Working time : Full time
• Length of contract : 18 months (with a possibility to reconduct)
• Start date: between 1st Nov. 2024 and 1st Jan. 2025

OUR OFFERSalary and grade depend on the level of experience. On the basis of a complete file, the ULiège Human Resources Administration can estimate the gross monthly salary.Full reimbursement of home/work journeys made by public transport and access to a range of for researchers are possible.HOW TO APPLYApplications (cover letter, a report on past research and detailed CV with full publication list) should be sent to Professors Maxime Fays, Frédéric Nguyen and Christophe Collette at the following address : , ,In the CV, please include the names and contacts of at least two people who can be contacted to provide letters of reference.SELECTION PROCEDURESelected candidates will be invited to an interview in English at the University of Liège or online via Teams or Zoom.Our institutional policy is based on diversity and equal opportunities. We select candidates based on their qualities, regardless of their age, sexual orientation, origin, beliefs, disability or nationality.CONTACT DETAILS AND FURTHER INFORMATIONFor further information on the nature of the tasks or the procedure: , ,Information on the processing of your personal dataThe personal data collected follow your application will be processed by the Faculty of Sciences and the School of Engineering of the University of Liege for the purpose of organizing the selection and recruitment.These data will be processed based on the execution of pre-contractual measures (art. 6-1, b. of the RGPD)These data will be kept for the duration of the selection procedure and, at the most, 9 months after the publication of the job offer. This data will not be passed on to third parties.In accordance with the provisions of the General Data Protection Regulation (EU 2016/679), you may exercise your rights relating to this personal data (right of access, rectification, deletion, limitation, and portability) by contacting the ULiège DataProtection Officer ( – Mr. Data Protection Officer, Bât. B9 Cellule “GDPR”, Quartier Village 3, Boulevard de Colonster 2, 4000 Liège, Belgium). You also have the right to lodge a complaint with the Data Protection Authority , ).Where to apply WebsiteRequirementsResearch Field Computer science Years of Research Experience 4 – 10Research Field Engineering Years of Research Experience 4 – 10Research Field Environmental science Years of Research Experience 4 – 10Research Field Physics Years of Research Experience 4 – 10Research Field Physics Years of Research Experience 4 – 10Additional InformationWebsite for additional job detailsWork Location(s)Number of offers available 1 Company/Institute University of Liège (ULiège) Country Belgium City Liège Postal Code 4000 Street Place du Vingt Août 7Contact CityLiège WebsitePostal Code4000STATUS: EXPIREDShare this page

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Liège

Job date

Sat, 12 Oct 2024 23:19:39 GMT

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