General Notices

A shared ocen project is being executed by the Department of Civil and Environmental Engineering of The UWI St Augustine. A vacancy exists for a researcher to work with the team executing this project. Read on for more details on the project and the available position. 

Project Title: "Using Artificial Intelligence (AI) to Improve Coastal Resilience in Data-sparse Locations: Caribbean Region Case Study"

The project aims to address the impacts of climate change on coastal areas, emphasizing the threat posed to communities and marine ecosystems by flood and storm surges. Leveraging Artificial Intelligence (AI) for climate resilience, the project will utilize data- driven insights to guide decision-making, particularly in data-sparse locations such as the Caribbean. The key objectives include identifying alternative data sources for decision-making, predicting climate resilience of coastal locations, and determining optimal techniques to sensitize and educate vulnerable communities. Stakeholder engagement is central to the project, with a focus on accessing and exploring datasets, and the study's findings will be disseminated directly to key stakeholders and the wider Caribbean region.

Job Title: Machine Learning Researcher

Duration of Contract:  The contract will be for a period of 18 months, with the possibility of extension based on performance and available funding.

Expected Start Date: The successful candidate is expected to commence the contract on 1st April 2024.

Location: The successful candidate will be expected to execute the Contract in-person at The University of the West Indies, St Augustine Campus, Trinidad and Tobago, or to specified and agreed remote/hybrid arrangements. Note that the successful candidate must be readily available to work in The Republic of Trinidad and Tobago.

Responsibilities

The successful candidate will be responsible for the development and implementation ofmachine learning models, engage in research and innovation and documentation andreporting. Specific tasks include:

A. Develop and implement machine learning models

1. Utilize machine learning techniques to analyze and interpret environmental datarelated to coastal resilience.

2. Collaborate with interdisciplinary teams to integrate AI solutions into coastalresilience strategies.

3. Lead efforts in data preprocessing, feature engineering, and model evaluation.

B. Research and Innovation

1. Stay abreast of the latest advancements in machine learning and AI relevant tothe project.

2. Contribute innovative ideas and approaches to enhance the project's outcomes.

C. Documentation and Reporting

1. Document all methodologies, codes, and findings in a clear and organizedmanner.

2. Contribute to the preparation of reports, presentations, and scientific publications.

Qualifications

Candidates are expected to have qualifications as outlined below.

A. Education

1. Minimum of a Master's degree in Computer Science, Data Science, MachineLearning, or a related field.

B. Skills and Experience

1. Proven experience in machine learning projects, where a focus on environmentalor geospatial applications will be an asset.

2. Proficient in programming languages such as Python and experienced withrelevant ML libraries (e.g., TensorFlow, PyTorch).

3. Strong background in data analysis, statistical modeling, and feature extraction.

4. Excellent problem-solving skills and the ability to work independently.

5. Previous experience in projects related to coastal resilience or environmentalsustainability is an advantage.

The deadline for the submission of applications is Monday, March 11, 2024.

Click here for more information on the application process and the remuneration package.