A new position has just been opened in the group. We're looking for a postdoc in electrical engineering or someone with electrical engineering skills at the postdoc level, i.e. industrial or research experience. You can see the full text here: https://ece.au.dk/om-instituttet/ledige-stillinger/job/research-position-in-electrical-engineering-at-the-department-of-electrical-and-computer-engineering-aarhus-university The deadline for applications is June 22, 2023.
Several papers have been published recently. You can check out two new papers on steady state surface NMR: Griffiths, M. P., Grombacher, D., Liu, L., Vang, M. Ø. & Larsen, J. J. (2022). Forward Modeling Steady-State Free Precession in Surface NMR. IEEE Geoscience and Remote Sensing Letters, 60, . https://doi.org/10.1109/TGRS.2022.3221624 and Liu, L.,Griffiths, M. P., Vang, M. Ø., Grombacher, D. & Larsen, J. J. (2023). Signal Processing Steady-State Surface NMR Data, IEEE Transactions on Instrumentation and Measurement, 72,  10.1109/TIM.2023.3264033
There's also a cool new paper on modelling of TEM data: Asif, M. R., Foged, N., Bording, T. S., Larsen, J. J. & Christiansen, A. V. (2023). DL-RMD: a geophysically constrained electromagnetic resistivity model database for deep learning applications. Earth System Science Data, 15(3), 1389-1401, https://doi.org/10.5194/essd-15-1389-2023.
Six new students have joined the group. Aske Kurup Bredmose and Johnni Damgaard Jensen will be doing their bachelor thesis project on surface NMR transmitters, and Bjarke Holm Jørgensen will be working on a fluxgate magnetometers. Adam Louie Hekkel Vergara will do his master thesis working on analysis of TEM data. Aksel Steen Thomassen and Kristoffer Tranberg Christiansen will both be working on machine learning methods in surface NMR data processing.
We have just published a new paper showing how machine learning approaches can be used to speed up the removal of powerline noise in geophysical data sets. In the paper, we give examples with surface NMR data and time-domain induced polarization data, but the method is applicable to essentially any data set with powerline noise. Larsen, J. J., Lévy, L. & Asif, M. R. (2022). Removal of powerline noise in geophysical data sets with a scientific machine-learning based approach. IEEE Transactions on Geoscience and Remote Sensing, 60, . https://doi.org/10.1109/TGRS.2022.3223737.
Thomas Kyung Dueholm Jensen and Mads Christian Rosendahl have both started their master thesis project in the group working with processing of surface NMR data.
Frederik Thomsen and Lukas Kezic have started on their bachelor thesis project in the group. They will be working with instruments for time-lapse resistivity measurements.
Khuram Naveed is a new postdoc in the group. His primary focus will be signal processing of time-domain induced polarization data.
The steady-state surface NMR concept allows us to manipulate the NMR signal in many different way. Check out this new paper for some impressive results: Grombacher, D., Griffiths, M. P., Liu, L., Vang, M. & Larsen, J. J. (2022). Frequency Shifting Steady-State Surface NMR Signals to Avoid Problematic Narrowband-Noise Sources. Geophysical Research Letters, 49(7), [e2021GL097402]. https://doi.org/10.1029/2021GL097402.
Claes Eske Harbo Jensen has joined the group for his bachelor thesis project, where he will work with remote reference noise cancellation on surface NMR data.
We have recently developed a new way steady-state surface NMR, which is a new way of doing surface NMR measurements. We see amazing increases in signal-to-noise ratio and mapping speed. Our paper "Steady-state surface NMR for mapping of groundwater" has just been published in Geophysical Research Letters: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021GL095381
In recent papers we have shown how spectral analysis is a highly efficient signal processing tool for surface NMR data, but we only did so with data recorded with our own Apsu instrument. In a new paper just published in Geophysical Journal International, we show how data acquired with the commercial instruments from Vista Clara and Iris Instruments can also be improved with spectral analysis https://doi.org/10.1093/gji/ggab472
We have just opened a call for a new 2-year postdoc in the group. The postdoc will work on instrument development and signal processing in DCIP, TEM and surface NMR. Read the full call text and apply here before December 13, 2021: https://www.au.dk/om/stillinger/job/postdoc-for-instrument-development-and-signal-processing-with-applications-in-groundwater-research
The tri-annual MRS workshop has taken place in Strassbourg, France. We had six on-site presentations focusing on our new steady-state surface NMR method, instrument development and signal processing.
Today, our paper "Fast removal of powerline harmonic noise from surface NMR data sets using a projection-based approach on graphical processing units" was published in IEEE Geoscience and Remote Sensing Letters, DOI: 10.1109/LGRS.2021.3118064.
Today, the invited talk "Apsu - A compact surface NMR instrument for groundwater investigations" was presented (online) at the International Meeting for Applied Geoscience & Energy.
Anders Kjær-Rasmussen has started on his Master Thesis project. Anders will be working on the signal processing side of steady-state surface NMR.
The paper "Efficient numerical Bloch solutions for multi-pulse surface NMR" has just been accepted for publication in Geophysical Journal International, DOI: 10.1093/gji/ggab321.
We have recently published two papers on the application of machine learning based methods in TEM. The first paper is concerned with data normalization, "Effect of Data Pre-Processing on the Performance of Neural Networks for 1-D Transient Electromagnetic Forward Modeling", IEEE Access, DOI: 10.1109/ACCESS.2021.3061761. The second deals with faster inversion."A neural network based hybrid framework for least squares inversion of transient electromagnetic data", IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2021.3076121.
Nikhil B. Gaikwad has started as a postdoc in the group. Nikhil is funded by the Villum Experiment project and will be working on the instrument side of this project.
We are looking for a skilled postdoc to join the research group. The 3-year position is concerned with signal processing and instrument development with transient electromagnetics. If you have a background in electrical engineering, (geo-)physics or similar, take a look at the position here:
Mathias Lønborg Friis has joined the group as a Master Thesis student. He will be working on spectral analysis of surface NMR signals and remote reference noise cancellation.
A new paper on gating of TEM data "Suppression of very low frequency radio noise in transient electromagnetic data with semi-tapered gates" was submitted to the open access journal Geoscientific Instrumentation, Methods and Data Systems. The paper is now in discussion at https://gi.copernicus.org/preprints/gi-2020-49/
Two new papers, one in induced polarization, one in magnetometry have recently been published. The first paper is "Automatic processing of time domain induced polarization data using supervised artificial neural networks" by Adrian Barfod, Léa Lévy and Jakob Juul Larsen in Geophysical Journal International, https://doi.org/10.1093/gji/ggaa460. The second paper is "Efficient reduction of powerline signals in magnetic data acquired from a moving platform" by Andy Kass, Anders Vest Christiansen, Esben Auken and Jakob Juul Larsen in IEEE Transactions on Geoscience and Remote Sensing, https://doi.org/10.1109/TGRS.2020.3029658
We are looking for a skilled postdoc with a background in electrical engineering or similar for our new project. The deadline for applications to the 2-year position is October 26. [12-1-2021 update: the position has been filled.]
The Villum Foundation has today awarded us a Villum Experiment grant for a new project "Surface NMR with long excitation pulses - technicality of game changer?"
Rasmus Balling Langhoff and Martin Wohlert Kjær have joined the group as Master Thesis students. They will carry out a joint project advancing spectral analysis for surface NMR data.
Two papers on spectral analysis have been published recently. The first paper is "Inverting surface NMR free induction decay data in a voltage-time data space" by Grombacher et al. in Journal of Applied Geophysics, 172, 103869 (2020) https://doi.org/10.1016/j.jappgeo.2019.103869 The second paper is "Mitigating narrowband noise sources close to the Larmor frequency in surface NMR" by Grombacher et al. in IEEE Geoscience and Remote Sensing Letters, (2020) https://doi.org/10.1109/LGRS.2020.3000639.
Matthew Griffiths has started as a PhD student in the group. Matt is funded by the Flood and Drought project and will be working on surface NMR.
Our new server with four 2080 TI GPUs is now up and running.
Rizwan Asif started as postdoc in the group. Rizwan is funded by the MapField project and will be working on machine-learning based processing of tTEM data.
Two papers "Apsu - A new surface NMR instrument for hydrogeophysics" and "Detection of capacitive couplings in groundbased TEM data with neural networks" was presented. The second paper is based on results obtained by Toke Frederiksen in his master thesis.
Anders Kjær-Rasmussen has started his bachelor thesis project in electrical engineering in the group. The aim of Anders' thesis work is speed-up and automated quality assurance of powerline harmonic removal in geophysical data sets (mainly surface NMR and DCIP).
The project ”Flood and Drought – Tracking Water in the Shallow Subsurface” has just been funded by Independent Research Fund Denmark. Besides the funding from Independent Research Fund Denmark, the project is also supported by co-funding from the Public Consultancy Committee at the Department of of Engineering. The project is a collaboration with Department of Geoscience. In the project, we will develop new methodology for faster surface NMR measurements using advanced NMR pulses and pulses sequences combined with new signal processing algorithms. The faster measurements will allow us to acquire denser NMR data sets, which in turn will be used to constrain hydrological models. Two PhD students will be recruited for the project and the positions will soon be announced.
Surface NMR suffers from a low signal to noise ratio in most areas of interest. We have recently developed a new signal processing methodology, spectral analysis, based on sliding window Fourier transform which can significantly improve signal to noise ratio and our first paper on this topic has now been published: “Complex envelope retrieval for surface nuclear magnetic resonance data using spectral analysis” by Lichao Liu, Denys Grombacher, Esben Auken and Jakob Juul Larsen, Geophysical Journal International, Volume 217, Issue 2, May 2019, Pages 894–905, https://doi.org/10.1093/gji/ggz068
Adrian S. Barfod is a new post doc in the group. Adrian will work on the Innovation Fund Denmark sponsored GIRem project. His main area is the development of automated machine-learning based tools for processing and sorting of cross-borehole direct current induced polarization data.
Toke Frederiksen and Erik Borum are two new master thesis students in the group. Toke's thesis work is concerned with automated detection of coupled tTEM data using neural networks. Erik's thesis work will expand the theoretical framework and applicability of spectral analysis for surface NMR.
Our new paper on the Apsu surface NMR receiver system has just been published as open access in Geoscientific Instrumentation, Methods and Data Systems, https://www.geosci-instrum-method-data-syst.net/8/1/2019/
Ejlskov A / S and Aarhus University work together to develop a faster, cheaper and easier method for cleaning contaminated soil without the need for excavators. Real-time 3D scanning of the subsoil allows biotechnological cleansers to be injected accurately into the contaminated underground, as well as monitoring simultaneously how the cleansers distribute in the soil. The project is funded by the Innovation Fund's Grand Solutions with an amount of almost 17 million. DKK.
Ny teknologi skal gøre det muligt at bestemme hvordan undergrunden under den enkelte mark naturligt omsætter kvælstof. Det vil bane vejen for målrettet regulering af kvælstofgødskning, til gavn for både miljø og landbrug.