Website:
nireekshan.ai
Job details:
Required Qualifications
· Education: M.Tech / M.Sc./ PhD in GIS, Geoinformatics, Remote Sensing, Civil Engineering, or a related spatial science field.
· Experience: 2 - 3 years of professional or serious academic project experience in GIS and remote sensing application development.
· Location: Kozhikode, Kerala
Key Responsibilities:
- Time-Series SAR Processing: Automate the ingestion and processing of Copernicus Sentinel-1 (C-band) and ISRO/NASA NISAR (L-band) data to generate high-resolution, state-wide InSAR ground subsidence maps.
- Dielectric Moisture Extraction: Implement dual-polarization techniques to decouple surface roughness and vegetation attenuation, isolating genuine shifts in complex soil dielectric permittivity to map subsurface seepage and piping.
- Algorithmic Data Fusion: Translate heavy raster datasets into discrete vector units, performing the zonal statistics necessary to compute our various soil based indexes at a decided area/ length.
- API & Cloud Integration: Build robust, automated pipelines querying ISRO's Bhoonidhi (EOS-04/NISAR) and NASA Earthdata (ASF DAAC) to continuously feed intelligence into our predictive engine.
- Help organize, georeferenced drone captured thermal, NDVI, and RGB orthomosaics into spatial databases for anomaly detection.
💡 Who We Are Looking For:
- Deep expertise in SAR/InSAR processing techniques (phase unwrapping, coherence tracking, SBAS/PS-InSAR methodologies).
- Strong proficiency in spatial Python libraries (GDAL, Rasterio, GeoPandas, Xarray, Shapely) and cloud-native geospatial processing.
- GIS Tools & Scripting: Proficiency in QGIS, ArcGIS, GDAL/OGR, and practical Python scripting for spatial automation (GeoPandas, Shapely, Rasterio).
- A solid scientific understanding of hydrological monitoring and geotechnical remote sensing.
- Working knowledge of Sentinel-1 SAR archives (SLC, GRD) into subsidence maps and backscatter time series using open-source pipelines - SNAP, ISCE.
- Working Knowledge of SMAP mission data processing.
- Experience with PS-InSAR / SBAS time series (MintPy, StaMPS), Exposure to computer vision or ML models for aerial imagery will be addon.
This is a unique opportunity to push the boundaries of civil infrastructure monitoring and build a life-saving disaster management digital twin from the ground up.
📍 Location: Kozhikode, Kerala 📩 How to Apply: Send your resume and a portfolio/GitHub link showcasing your SAR processing capabilities to [nireekshandynamics@gmail.com], or DM me directly!. Apply before 15 August 2026.
Compensation: Commensurate with qualification, experience and market
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