Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Harvard University
- INESC ID
- LINGNAN UNIVERSITY
- Nanyang Technological University
- RMIT UNIVERSITY
- University of Maryland, Baltimore
- Wayne State University
- AbbVie
- Center for Drug Evaluation and Research (CDER)
- City of Hope
- FCiências.ID
- Florida Atlantic University
- Hong Kong Polytechnic University
- Institute of Computer Science CAS
- Instituto Superior Técnico
- Nature Careers
- Northeastern University
- OsloMet
- RMIT University
- SciLifeLab
- Singapore University of Technology & Design
- UNIVERSITY OF SOUTHAMPTON
- Universidade de Coimbra
- University of Bergen
- University of Birmingham
- University of Michigan
- University of New South Wales
- University of Oslo
- University of St Andrews;
- Zintellect
- 21 more »
- « less
-
Field
-
Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
-
driven inverse design of functional materials. Current research directions include: Reversible material representation methods for accelerated inverse design Large language, diffusion & graph neural models
-
, group theory, and/or graph theory will be necessary. Experience in modelling biological processes, and in algorithm development or computation will also be valuable. Proven commitment to proactively
-
-graph inference. Ensure the system is deployment-ready by supporting benchmarking of inference speed, compute efficiency, and scalability with concurrent agents. Maintain high software engineering
-
advanced light microscopy data. The lab’s research scope ranges from reinforcement learning for drug design, interpretable ML pipelines for cancer research and diagnosis as well as graph neural networks
-
machine learning and deep learning methods, including architectures such as Transformers, RNNs, and CNNs, and related models used for sequence, image, graph, or multimodal data. Demonstrated experience
-
decision agents based on graph neural network or similar will an advantage. Key Competencies Good knowledge in reliability analysis. Experience in FMECA and equipment health management will be advantageous
-
. Current research directions include: Reversible material representation methods for accelerated inverse design Large language, diffusion & graph neural models for materials discovery Fine tuning and
-
machine learning and deep learning methods, including architectures such as Transformers, RNNs, and CNNs, and related models used for sequence, image, graph, or multimodal data. Demonstrated experience
-
Framework (IMF) based on ISO 81346, the research proposes the extension of IMF with an explicit temporal aspect, enabling time-aware system modeling and the creation of a unified system knowledge graph