Total 2 job vacancies by A*star Research Entities

Digital Supply Chain Group of the Resilient Value Chain Division at the ARTC is searching for a Development Scientist who will lead and support projects in Supply Chain innovation using advanced data analytics, Generative AI and SOTA AI.

Responsibilities:

1. Deliver tangible outcomes in technical projects: e.g:Develop new, bespoke, accurate, and fast algorithms to solve Supply Chain optimization and prediction problems. Implement state-of-the-art approaches and bring them to industry-readiness status.
2. Focus on technical efforts in data analytics, Generative AI and SOTA AI research by providing effective tech leadership in problem definition and solution design. Key skillsets include Statistical Analysis, Neural Network Frameworks, GANs (Generative Adversarial Networks), Natural Language Processing, Data Generation and Augmentation, Hyperparameter Tuning.
3. Continuously develop personal technical skillsets to ensure technical relevance.
4. Domain knowledge (aerospace, energy, land transport, logistics, etc.) for the specific context of operational research.
5. Abide by software development processes and procedures to ensure high quality of deliverables.
6. Assist in securing industry projects and research grants through stakeholder engagements.

Job Requirements:

• Good interpersonal and communication (verbal & written) skills.
• PhD in Computer Engineering, Computer science, Supply Chain Analytics, or Business Analytics.
• Strong skills in mathematical problem definition, algorithm design, scientific computing, statistic modeling and analytics, and real-world problem solving.
• Strong scientific programming background (e.g. Pyton, C, C++, etc.) with familiarity with machine learning frameworks (e.g. TensorFlow/Pytorch/Scikit-learn).
• Prior experience with AI in supply chain optimisation (e.g., fleet planning, network design, scheduling) is preferrable.
• A publication track record in Industry 4.0-related topics, e.g., Gen-Ai, optimisation, machine learning/deep learning, etc.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

Digital Supply Chain Group of the Resilient Value Chain Division at the ARTC is searching for a Development Scientist who will lead and support projects in Supply Chain innovation using advanced data analytics, Generative AI and SOTA AI.

Responsibilities:

1. Deliver tangible outcomes in technical projects: e.g:Develop new, bespoke, accurate, and fast algorithms to solve Supply Chain optimization and prediction problems. Implement state-of-the-art approaches and bring them to industry-readiness status.
2. Focus technical efforts in data analytics, Generative AI and SOTA AI research by providing effective tech leadership in problem definition and solution design. Key skillsets include Statistical Analysis, Neural Network Frameworks, GANs (Generative Adversarial Networks), Natural Language Processing, Data Generation and Augmentation, Hyperparameter Tuning.
3. Continuously develop personal technical skillsets to ensure technical relevance.
4. Domain knowledge (aerospace, energy, land transport, logistics, etc.) for the specific context of operational research.
5. Abide by software development processes and procedures to ensure high quality of deliverables.
6. Assist in securing industry projects and research grants through stakeholder engagements.

Job Requirements:

• Good interpersonal and communication (verbal & written) skills.
• PhD in Computer Engineering, Computer science, Supply Chain Analytics, or Business Analytics.
• Strong skills in mathematical problem definition, algorithm design, scientific computing, statistic modeling and analytics, and real-world problem solving.
• Strong scientific programming background (e.g. Pyton, C, C++, etc.) with familiarity with machine learning frameworks (e.g. TensorFlow/Pytorch/Scikit-learn).
• Prior experience with AI in supply chain optimisation (e.g., fleet planning, network design, scheduling) is preferrable.
• A publication track record in Industry 4.0-related topics, e.g., Gen-Ai, optimisation, machine learning/deep learning, etc.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.