Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- Zintellect
- Indiana University
- City of Hope
- INESC TEC
- King's College London
- Nanyang Technological University
- National University of Singapore
- University of Bergen
- University of British Columbia
- University of Sydney
- Cellular and Molecular Therapeutics Branch, NHLBI, NIH
- Center for Biologics Evaluation and Research (CBER)
- Fields Institute
- Florida Atlantic University
- Hong Kong Polytechnic University
- Lawrence Berkeley National Laboratory
- UNIVERSITY OF SYDNEY
- Universidade de Coimbra
- University of Birmingham
- University of California
- University of London
- University of Michigan
- University of Notre Dame
- University of Rhode Island
- University of Stavanger
- University of Sussex;
- University of Waterloo
- Università degli Studi di Padova
- 18 more »
- « less
-
Field
-
or more of the following is preferred: flow cytometry, CRISPR-based gene perturbation, viral vector systems, mouse models, xenograft models, next-generation sequencing-based assays, immunologic assays
-
: • Develop real-time optimization algorithms; • Model multi-vector energy-water-hydrogen systems; • Support the development of digital twins; • Test the algorithms using operational data; • Prepare a technical
-
. The prospective candidate should have the knowledge to perform cell culture works and a willingness to learn and trouble shoot new techniques. Required skills: · Cell culture · Viral vector production
-
to mentorship from experts in relevant mathematical areas as well as AI safety researchers affiliated with PrincInt, the Schwartz Reisman Institute for Technology and Society, and the Vector Institute
-
Responsibilities Architect and implement large-scale, georeferenced 3D digital twin models Develop computational pipelines for integrating vector, raster, terrain, LiDAR, and photogrammetric data Design procedural
-
will be affiliated with the Energy Systems Engineering Group. The position focuses on developing autonomous AI-based optimization and control methods for a multi-vector hybrid microgrid that supports