Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- European Space Agency
- Argonne
- Stony Brook University
- Technical University of Denmark
- Technical University of Munich
- Oak Ridge National Laboratory
- Boston University
- Heriot Watt University
- IMT
- KINGS COLLEGE LONDON
- Leibniz
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- NEW YORK UNIVERSITY ABU DHABI
- National Renewable Energy Laboratory NREL
- Nature Careers
- UNIVERSITY OF HELSINKI
- University of Southern California
- University of Washington
- Vrije Universiteit Brussel
- Yale University
- 10 more »
- « less
-
Field
-
trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell
-
related field in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in
-
in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in programming (e.g
-
related field in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in
-
to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies. This is an exciting
-
missions. 6) Crypto key management and adaptation of post-quantum cryptography (PQC) Developing robust key management protocols to ensure secure generation, distribution, and storage of cryptographic keys in
-
project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
-
machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
-
analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive
-
) and cover a wide range of innovative topics, from the development and validation of novel methods, algorithms and EO products to innovative climate research; the development of improved climate data