Research Engineer/Associate (DoE SES)

We are seeking an experienced candidate to join our team for a solar resource assessment and forecasting project. Our team has extensive expertise in solar resource assessment, real-time monitoring, and solar forecasting, and we have recently completed a large-scale project to advance solar forecasting in the region. The project has been implemented into a fully automated operational system, which completed trial phase, and we are continuously working to improve it.
The selected candidate will have the opportunity to work closely with highly experienced professionals in the cutting-edge field of fast-paced solar forecasting and resource assessment. The daily work routine will involve developing various algorithms, including but not limited to machine-learning models, satellite image processing models, coding, code optimization, and implementation of real-time forecast post-processing models. Additionally, as part of the project, our client requires on-site support for the system, and we are looking for candidates with programming and troubleshooting experience to join our team. The candidate will also play a key role in supporting the future strategic goals and
developments for improving solar forecasting software.
· DevOps and software engineering responsibilities.
· Responding technical queries and bug fixing of solar forecasting tool.
· Contributing the scientific development of solar forecasting and additional software.
· Supporting, developing, maintenance and troubleshooting of solar forecasting code base, MySQL databases, docker containers, GIT, and PBSpro
· Supporting, developing, maintenance and bug fixing of inbound and outbound data streams
· Further develop the solar forecasting model.
· Implementing advanced logging and real-time monitoring tools for the forecasting system
· Maintenance and administration of existing and new physical servers
· Supporting any other IT and server related issues that might arise
· Supporting (or eager to learn) the development of new technologies including but not limited to spatial data analysis, satellite image processing, advanced machine-learning algorithms for forecasting, post-processing to further improve forecast accuracy.
· Supporting the development of additional tools to improve SERIS’ offering and product portfolio.
· Supporting cloud integration of solar forecasting model.
· Supporting the future of the Digitisation of Energy’s strategic goals for solar forecasting in the region.

· Bachelor degree for research engineer position in Engineering, Computer Science, IT, Systems Analysis, a Quantitative field, or other related field.
· Master degree in Engineering, Computer Science, IT, Systems Analysis, a Quantitative field, or other related field is required for research associate position.
· Intermediate/advanced Python knowledge
o Experience in writing Python scripts
o Experience in debugging and troubleshooting in Python.
o Experienced with the data science Python packages, e.g., Pandas, Numpy, SciKit-Learn, Xarray, Matplotlib
· Intermediate/advanced Redhat/CentOS Linux Experience preferred, RHCSA preferred. RHCE is a plus.
· Experience in writing and troubleshooting OS Level Scripts and OS Level Commands.
· Experienced with MySQL for Database management as well as writing queries.
· Experience with GIT, version control and CI/CD.
· Experience with PBSPro (preferred) or eager to learn.
· Experience with Docker containers and their maintenance.
· Experience with software technical support, troubleshooting and debugging is preferred.
· Experience with basic networking is preferred.
· Experience with production-level coding, API design and implementation, and AWS experience.
· Eager to learn machine-learning, regression, image processing (experience is preferred).
· Ability to work independently with a strong sense of initiative.
· Highly motivated, self-starter and well organized.
· Willing to do on-site support for clients.

Location: Kent Ridge Campus

Organization: Solar Energy Research Inst of S'pore

Department : Research Cluster

Employee Referral Eligible: No

Job requisition ID : 24744