Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
PhD Student in Building Materials Lulea Reference number 3267-2026 Are you ready to take the next step in your academic journey? As a doctoral student with us, you will work closely with leading
-
relevant social science expertise. You should demonstrate: Essential Criteria: A PhD, or close to completion, in Political Science, Media and Communication, Sociology or a related social science field
-
chemical and isotopic characterization of groundwater within the aquifer system of the Gorgoglione mining concession (MT), integrating hydrogeochemical and agro-environmental aspects through a
-
Icahn School of Medicine at Mount Sinai - The Institute for Genomic Health | New York City, New York | United States | 26 days ago
, health system researchers, and disease-area experts who share a single goal: translating large-scale genomic data into new paradigms for human health. Current arenas of IGH research include mining deep
-
combining artificial intelligence with human expertise. The lab develops knowledge-grounded artificial intelligence, text mining and knowledge assembly, mathematical and systems modeling, and causal
-
Biology Department Posting Number R260153 Posting Link https://www.ubjobs.buffalo.edu/postings/64378 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary
-
and Agentic AI Research Centre (CIAA) Pattern Recognition/Machine Learning/Deep Learning/Reinforcement Learning, LLM/MLLM, Generative AI, Neural Graphics, Graph Mining, Data Mining, AI agent, Natural
-
multi-omics data, including WGS, WES, DNA methylation, RNA-seq, proteomics, lipidomics and metabolomics in large-scale human populations. The lab is interested in integrating and mining the different
-
multi-omics data, including WGS, WES, DNA methylation, RNA-seq, proteomics, lipidomics and metabolomics in large-scale human populations. The lab is interested in integrating and mining the different
-
advanced data‑mining and machine‑learning methods. The expected scientific outcome is to establish guidelines for identifying and optimizing promising electrolyte materials and to support the