Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE). For additional information, please contact Prof. Dr. Erik Koffijberg
-
of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
-
for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
-
well as the clinical activities at the Karolinska University Hospital, unique access to international expertise in machine learning, state-of-the-art imaging, diverse patient cohorts, and relevant computational
-
ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI
-
, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
-
Supervisors: Dr Raj Pandya, Prof. Nicholas Hine, Prof. Reinhard Maurer While we as humans are used to seconds and hours, electrons and atoms in materials move a whole lot faster around a million
-
the PhD candidate may include (non-)linear inverse load estimation and data-driven/machine learning techniques that rely on physics-informed guidance for improved robustness. A key task will be to quantify
-
, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
-
Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression