Data Scientist: Graph Neural Networks
1 month ago
At Bosch, we are seeking a highly motivated and talented Data Scientist to join our team as an Intern in the field of Graph Neural Networks. As a Data Scientist, you will be responsible for assisting in the research, design, and implementation of Graph Neural Networks (GNNs) and related models for real-world problems.
Key Responsibilities:- Develop and implement node embedding techniques (DeepWalk, Node2Vec, GraphSAGE) to generate high-quality vector representations for graph nodes.
- Work with large-scale graph-structured data in the domain of sustainability.
- Modify ontology to address use-cases.
- Participate in experiments to test new graph-based machine learning methods, optimizing for both performance and accuracy.
- Collaborate with team members to integrate graph-based models into existing machine learning pipelines and production systems.
- Stay up-to-date with the latest research and advancements in the field of graph-based machine learning.
- Enrolled in a relevant undergraduate or graduate program in Computer Science, Information Science, Data Science, or a related field.
- Strong understanding of knowledge graph concepts, ontologies, and semantic technologies.
- Proficiency in programming languages such as Python, Java, or RDF-based languages.
- Familiarity with data integration, linked data principles, and graph databases (RDF, OWL).
- Familiarity with Graph Theory and Machine Learning such as Graph Neural Networks (GNNs), Graph Convolutional Networks (GCNs), Graph Attention Networks (GATs), or similar models.
- Basic understanding of node embedding techniques like DeepWalk, Node2Vec, or GraphSAGE
- Experience with graph database systems and query languages (SPARQL).
- Strong analytical and problem-solving skills.
- Effective communication and collaboration skills in a team environment.
- Eager, quick learner with a strong team-work spirit.
- Candidate should fulfill the visa requirements for employment in Singapore.
- Applicant must be enrolled in full-time studies throughout internship period, or plan to pursue further studies.
- Candidate should be available for full-time work for 4-6 months.
- For foreign students studying overseas, you must be eligible for the Work Holiday Programme (WHP).
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