Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- CNRS
- HONG KONG BAPTIST UNIVERSITY
- Technical University of Munich
- University of Luxembourg
- Binghamton University
- Bucharest Universty of Economic Studies
- DAAD
- Duke University
- The University of Chicago
- University of Innsbruck, Institute of Computer Science
- AALTO UNIVERSITY
- Aarhus University
- Academic Europe
- Babes-Bolyai University
- Brunel University
- CIC nanoGUNE
- CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto
- Fondazione Bruno Kessler
- Forschungszentrum Jülich
- Fundació per a la Universitat Oberta de Catalunya
- Heidelberg University
- Institute for Basic Science
- Institutionen för akvatiska resurser
- LIP - Laboratório de Instrumentação e Física Experimental de Partículas
- Lehrstuhl für Nachhaltige Thermoprozesstechnik und Institut für Industrieofenbau und Wärmetechnik
- Luxembourg Institute of Science and Technology
- Massachusetts Institute of Technology (MIT)
- Maynooth University
- MedUni Vienna
- Michigan State University
- Northeastern University
- Norwegian University of Life Sciences (NMBU)
- Swedish University of Agricultural Sciences
- Tampere University
- UNINOVA - Instituto de Desenvolvimento de Novas Tecnologias
- Universidad de Alicante
- Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab
- Universidade de Coimbra
- Universidade de Trás-os-Montes e Alto Douro
- University of A Coruña
- University of Bergen
- University of Cambridge
- University of Cambridge;
- University of Jyväskylä
- University of Pardubice
- University of Texas at El Paso
- Université Grenoble Alpes
- VSB - Technical University of Ostrava
- Vrije Universiteit Amsterdam
- Warsaw University of Technology - Centre for Credible AI
- 41 more »
- « less
-
Field
-
modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
-
will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
-
of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
-
to prepare project reports and co-author research papers. The ideal candidate is expected to be working towards a PhD in Computer Engineering, Computer Science, Computer Systems Engineering, Electronic
-
the rank of Research Assistant Professor in computational mathematics, machine learning, scientific computing, statistics, and related areas. The appointee is expected to conduct high-impact research
-
, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
-
should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural
-
of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
-
in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial. Experience in machine learning and neural networks is desirable. The successful applicant
-
Professor (25260446) Responsibilities: The Department is recruiting one scholar at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics