Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
-
Field
-
an emphasis on technology, data science and the humanities. We are seeking highly motivated individuals with a strong interest in cancer genetics and genomic medicine to join the research team under Associate
-
, Public Health, Climate Science, Data Science, or related disciplines. Demonstrated experience in managing large-scale data sets and conducting health-related research studies. Strong analytical skills with
-
agentic architecture. With prior experience in AI security and AI agents, including prompt injections, data extraction, jailbreaking, poisoning and adversarial attacks, the candidate brings transferable
-
Responsibilities: Conduct programming and software development for big data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
-
Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a
-
observations and video data coding. Experience of collating and organising large amounts of data (video/audio) Skills in or knowledge of managing/using a Network Attached Systems (NAS) to store data. Skills in
-
Cutting Theme 2 (Satellite Remote Sensing). The EOS-RS teams’ research covers SAR, multi/hyper-spectral remote sensing, LiDAR, and GNSS data for disaster response and hazard monitoring for earthquakes
-
. The Research Assistant/Research Associate will play a key role in technical and scientific work of unifying large scale genomic (WGS, GWAS, long read) and non genomic (EHR, lifestyle, clinical) data from
-
++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
-
the short to medium-term burden of infectious diseases across large spatial scales using high-frequency data. Key Responsibilities: Develop models to understand the epidemic potential and instantaneous