Company Overview:
Wilmar International Limited is Asia’s leading agribusiness group, involved in activities such as oil palm cultivation, edible oils refining, oilseeds crushing, consumer pack edible oils processing, specialty fats, oleochemicals, biodiesel manufacturing, and grains processing. With over 1,000 manufacturing plants and a vast distribution network covering China, India, Indonesia, and more than 50 other countries, Wilmar is supported by a multinational workforce of about 100,000 people.
Job Summary
We are currently recruiting a position for a Research Scientist to join Wilmar’s corporate lab (Wil@NUS). The potential candidate will be primarily involved in data analytics and machine learning. The project objectives are to model analytical data collected from Wilmar's factories or R&D centres using ML or AI for optimizing enzyme production.
Requirements:
- Team player and ability to communicate technical concepts to lay people
- Ability to code in a few languages - R, python, java, bash
- Knowledge in bioinformatics (sequence analysis, protein structure prediction)
- Knowledge in AI backend, e.g. tensorflow, pytorch
- Knowledge in optimizing ML or AI models to meet target specification
- Apt learner and versatile in applying new computational techniques to solve open problems
Main responsibilities of the incumbent (not limited to):
- Manage and preprocess data
- Code and script based on specified tasks
- Statistical analysis and machine learning experience in the following areas:
- Optimization algorithms
- Supervised learning
- Unsupervised learning
- Sampling algorithms
- Deep learning algorithms
- Summarizing results for reporting purposes
- Participate in seminars and research-in-progress meetings within the team and collaborators
- Write and publish scientific papers and patents
Qualifications:
· At least a PhD in any of the following areas: statistics, data science or computer science
Job renumeration commensurate to experience. Shortlisted candidates will be notified for an interview to discuss specific details.