Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
-
/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
-
urban scene, relatively affordable living, rich cultural offerings, and vibrant nightlife. Further questions regarding the open PhD positions can be discussed with the supervisor, Prof. Dr. Steven Travis
-
, machine learning, and information-theoretic approaches to achieve robust, non-intrusive security for the ever-expanding IoT landscape. Feature Engineering for Encrypted Traffic: It is crucial to identify
-
science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato
-
problems in biology by combining machine learning with in-depth knowledge of biological processes. Who we are looking for You have a Master in Science (Bioengineering, Biochemistry-Biotechnology, Biomedical
-
problems in biology by combining machine learning with in-depth knowledge of biological processes. Who we are looking for You have a Master in Science (Bioengineering, Biochemistry-Biotechnology, Biomedical
-
, analytical and computer programming skills. Advantage will be given to applicants with experience in one or more of the following: signal processing, deep learning, acoustics, psychoacoustics, acoustic
-
Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
Job Code: 18-25 Job Offer from June 04, 2025 The Department of Prof. Dr. Stefan W. Hell invites applications for a PhD position exploring AI approaches in optical science, molecular imaging and
-
the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning