68 machine-learning-"https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" Fellowship positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
image processing, disease detection, diagnosis, and therapeutic monitoring. The program addresses critical regulatory challenges posed by AI devices that can continuously learn and adapt, including
-
fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro
-
or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
-
design and discovery, including the use of artificial intelligence (AI) and machine learning (ML) techniques. The hired candidate will focus on computational aspects of immune repertoire analyses
-
About us The UCL Laboratory for Molecular Cell Biology (LMCB, http:/www.ucl.ac.uk/lmcb) is an internationally renowned, multidisciplinary, molecular and cell biology department, located in the heart
-
systems, and clinical perspectives, allowing the candidate to acquire valuable skills and establish a strong independent research profile. Please submit the following application materials
-
interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
-
, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
-
We have an exciting research opportunity for a Research Assistant / Associate tojoin our team. The post holder will be based at the Cancer Research UK-Scotland Institute (CRUK-SI) in Glasgow https
-
and a true passion for cutting-edge bench-to-bedside research are encouraged to apply and provide three professional references. LEARNING OBJECTIVES Trainees will perform basic and translational