About Data Extraction
A major challenge of current (big) data systems lies in the provision of high-quality information suited for downstream analysis purposes, given that the data at hand are often irrelevant, redundant, noisy, inconsistent, incomplete or unstructured.
Imec research groups at UGent and KU Leuven are devising innovative cleansing, completion and feature extraction approaches to extract reliable information from raw data.
How can we help you?
Some examples of what we have done
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Join the forward thinkersJob opportunities
Wearable Deep Learning Researcher
The candidate will mainly investigate how deep learning is leveraged for the design of sensor data processing algorithms that need to be robust for alternating product configurations and difference amongst users.
CEO for an imec Advanced Optical Sensors start-up
Driving the strategy, business and product roadmap.
Process Step Engineer CMP (Shifts)
Chemistry or Material Science professional to participate in a range of Chemical Mechanical Polishing development projects in our lab and clean room.
Postdoctoral Researcher on Design and Implementation of Phoxonic Micro/Nanosystems
Phoxonics: wave-based sensing and actuation.
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