Processed data, statistical outputs and model projections supporting research into freshwater inequality, spatial dependence and sustainability risks across Africa, with projections to 2030. This is a newer research-data release for water-resource planning, spatial analysis and sustainability research. The visible record does not enumerate the filenames, so inspect the archive contents before publishing the card.

WhatsApp with the word i’m interested, and the Application link will be sent to you. Geohubng Members only.

The responsibilities include:

Reviewing the accuracy and quality of GIS maps, satellite imagery products, geospatial datasets and analytical reports.

Evaluating remote-sensing methods, geospatial workflows and analytical techniques.

Providing technical recommendations for complex mapping and analysis problems.

Developing training materials and contributing to learning programmes with academic institutions.

Improving analytical procedures, documentation and AI-assisted geospatial workflows.

GeoHubNG Member opportunity only. Send Interested to info@geohubng.com

 

Job Responsibilities

Identify business and operational problems suitable for AI and digital solutions.

Work with business and plant teams to understand operational challenges and requirements.

Analyse and interrogate data to support AI and machine-learning initiatives.

Develop, test and evaluate analytical and machine-learning models.

Support the development and deployment of AI and digital solution prototypes.

Monitor the performance of deployed AI and digital solutions.

Apply AI, machine learning and advanced analytics to improve productivity, reliability, safety and decision-making.

Translate technical outputs into clear operational and commercial recommendations.

Work closely with engineers, operators and plant leadership across the Group.

Support the Group AI & Digitisation programme and its implementation across business units and plants.

A national flood and drought monitoring resource combining ground observations, satellite information and modelled climate and hydrological data for near-real-time monitoring and forecasting of hydrological variability in Nigeria. The system provides access to maps, time series, summary statistics and warning information for current and potential future flood and drought conditions. Publisher: UNESCO Intergovernmental Hydrological Programme Water Information Network System (IHP-WINS).

The Sahel is mostly covered in grassland and savanna, with areas of woodland and shrubland. Grass cover is fairly continuous across the region, dominated by annual grass species such as Cenchrus biflorus, Schoenefeldia gracilis, and Aristida stipoides. Species of Acacia are the dominant trees, with Acacia tortilis the most common, along with Acacia senegal and Acacia laeta. Other tree species include Commiphora africana, Balanites aegyptiaca, Faidherbia albida, and Boscia senegalensis. In the northern part of the Sahel, areas of desert shrub, including Panicum turgidum and Aristida sieberana, alternate with areas of grassland and savanna. During the long dry season, many trees lose their leaves, and the predominantly annual grasses die.