Sort by
Refine Your Search
-
Listed
-
Country
-
Field
- Computer Science
- Economics
- Engineering
- Business
- Medical Sciences
- Arts and Literature
- Education
- Design
- Biology
- Materials Science
- Science
- Linguistics
- Mathematics
- Earth Sciences
- Law
- Psychology
- Electrical Engineering
- Social Sciences
- Philosophy
- Sports and Recreation
- Humanities
- Physics
- Chemistry
- Environment
- 14 more »
- « less
-
About the Opportunity JOB SUMMARY The Sr Machine Learning (ML) Engineer applies expertise in deploying and scaling AI pipelines across at least one major cloud platform (AWS, GCP, or Azure
-
to specialise in one or more areas of expertise such as, but not limed to, networking & telephony, cloud, and security. Providing an excellent experience for both staff and students the role holder
-
, including word processing, databases, spreadsheets, email and cloud-based systems. Salary details Appointment to this role will be at HEO 5 and will have a total remuneration package of up to $105,665
-
Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/39543 Job Number SE192824 Position Information Department or Unit Name College
-
/or Cloud Computing. You bring current industry expertise, such as network security frameworks (e.g., CCNA Network Security) or cloud platforms (e.g., AWS), and are passionate about sharing your
-
(Docker, CI/CD scripts) and support cloud/HPC model training. Plan, run and analyze pilot studies (SME pilots and lab validation); participate in data collection, annotation and lab assay coordination
-
. Indicative Areas of Expertise Artificial Intelligence & Machine Learning Data Science & Big Data Analytics Software Engineering & Full Stack Development Cloud Computing & Distributed Systems Cybersecurity
-
: TCP/IP communication, real-time and multi-threaded client-server models e. Secure coding and encryption: HTTPS, TLS, AES, HMAC, and secure transmission protocols f. Cloud infrastructure and services
-
-enabled solutions and advanced modeling, to improve the quality and utility of datasets and enable new analytic capabilities; Ingesting structured and unstructured datasets into Google Cloud Platform (GCP
-
surface, aerosols, clouds, and climate change. In-house capabilities include design and development of novel airborne instruments for aerosol, cloud and trace gases systems. For the past year, we hosted a