Chastity AIKEN
2022-03-10 09:15:30
Institution: Ifremer, Centre de Bretagne
Open Until: 2022-03-31
Ifremer seeks a post-doctoral researcher to develop signal processing and machine learning techniques to classify and separate signals recorded by ocean bottom seismometers (OBS) to enhance earthquake waveforms and microseismic noise. The position is part of the Agence Nationale de Recherche (ANR) BRUIT-FM project, coordinated by Wayne Crawford at IPGP. However, BRUIT-FM gathers experts in seismology, acoustics, oceanography, and signal processing from French research organizations or laboratories (IPGP, Ifremer, SHOM, UBO, ESIEE/IFPEN, GIPSA-Lab, ENSTA), one industrial partner (iXblue) developing the technology of a rotational seismometer, and international experts from GEOB3N (Spain) and LDEO (USA).
The candidate is expected to characterize main features of non-seismic signals recorded by OBSs in time, frequency, time-frequency/scale, and multi-sensor domains to define specific patterns to be isolated and removed. The targeted non-seismic signals are both of low and high frequency that may overlap with earthquake and microseism signals. Targeted signals to isolate/remove in the low frequency spectrum (< 1 Hz) include compliance noise generated by ocean waves and amplitude-varying noise induced by bottom currents and, in the high frequency spectrum (> 1 Hz), marine mammal vocalizations and ship noise. The candidate is expected to develop algorithms that can characterize, detect, and remove these types of non-seismic signals from OBS recordings.
The position is located at the Centre de Bretagne, Ifremer (Institut Français pour Recherche de l’Exploitation de la Mer) in Plouzané, France. The candidate will be supervised by Stéphan Ker (stephan.ker<at>ifremer.fr) and Laurent Duval (laurent.duval<at>ifpen.fr). A successful applicant is expected to have a PhD with strong interest in spectral analysis, adaptive filtering, and machine learning with proficient coding skills in C/C++, Python/Matlab, or a similar programming language. French language proficiency is not required for this position.
The appointment will be for 16 months. Interested persons are directed to contact Stéphan Ker (stephan.ker<at>ifremer.fr) with a single PDF with a cover letter, CV, and contact information for references. Deadline to apply is March 31, 2022. Expected start date is Spring 2022 but open to negotiation.
Open Until: 2022-03-31
Ifremer seeks a post-doctoral researcher to develop signal processing and machine learning techniques to classify and separate signals recorded by ocean bottom seismometers (OBS) to enhance earthquake waveforms and microseismic noise. The position is part of the Agence Nationale de Recherche (ANR) BRUIT-FM project, coordinated by Wayne Crawford at IPGP. However, BRUIT-FM gathers experts in seismology, acoustics, oceanography, and signal processing from French research organizations or laboratories (IPGP, Ifremer, SHOM, UBO, ESIEE/IFPEN, GIPSA-Lab, ENSTA), one industrial partner (iXblue) developing the technology of a rotational seismometer, and international experts from GEOB3N (Spain) and LDEO (USA).
The candidate is expected to characterize main features of non-seismic signals recorded by OBSs in time, frequency, time-frequency/scale, and multi-sensor domains to define specific patterns to be isolated and removed. The targeted non-seismic signals are both of low and high frequency that may overlap with earthquake and microseism signals. Targeted signals to isolate/remove in the low frequency spectrum (< 1 Hz) include compliance noise generated by ocean waves and amplitude-varying noise induced by bottom currents and, in the high frequency spectrum (> 1 Hz), marine mammal vocalizations and ship noise. The candidate is expected to develop algorithms that can characterize, detect, and remove these types of non-seismic signals from OBS recordings.
The position is located at the Centre de Bretagne, Ifremer (Institut Français pour Recherche de l’Exploitation de la Mer) in Plouzané, France. The candidate will be supervised by Stéphan Ker (stephan.ker<at>ifremer.fr) and Laurent Duval (laurent.duval<at>ifpen.fr). A successful applicant is expected to have a PhD with strong interest in spectral analysis, adaptive filtering, and machine learning with proficient coding skills in C/C++, Python/Matlab, or a similar programming language. French language proficiency is not required for this position.
The appointment will be for 16 months. Interested persons are directed to contact Stéphan Ker (stephan.ker<at>ifremer.fr) with a single PDF with a cover letter, CV, and contact information for references. Deadline to apply is March 31, 2022. Expected start date is Spring 2022 but open to negotiation.
