24 parallel-processing-"INSERM" Postdoctoral positions at THE UNIVERSITY OF HONG KONG
Sort by
Refine Your Search
-
concentrate on three interrelated areas: a) Semiconductor Equipment Scheduling: In semiconductor fabs, a vast number of wafers are processed across hundreds or even thousands of manufacturing tools following
-
wafers are processed across hundreds or even thousands of manufacturing tools following highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences
-
proficient in data analysis using statistical or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic
-
or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic research papers. They should be organized, self
-
slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
-
. Preference will be given to those with expertise in innovative methods of advanced statistics and/or learning analytics, such as multiple linear regression, mediation analysis, mixed-effect models, process
-
, Marine Science, Computer Science, or related fields (obtained within the last 2 years). Strong research record with publications. Experience in programming, satellite data processing, and/or fieldwork
-
of Professor Khuloud Al-Jamal, a Chair of Drug Delivery and Nanomedicine. The aim of our lab is to use nanotechnology to better understand, diagnose and treat diseases with particular interests in cancer and
-
to better understand, diagnose and treat diseases with particular interests in cancer and neurodegenerative diseases. We are a highly collaborative and multidisciplinary lab eager to create an impact on
-
methods of advanced statistics and/or learning analytics, such as multiple linear regression, mediation analysis, mixed-effect models, process mining, epistemic network analysis and cluster analysis