Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
opportunities to develop research profile, to travel to give demos and presentations, and to write academic papers. Candidates should hold a PhD degree in Computer Science or other relevant discipline. The
-
taken into consideration. A suitable candidate will have a PhD in sociology, computer science, economics, statistics, political science or a corresponding subject of relevance to computational social
-
, Linguistics and Media and Journalism Studies. For this role, we are looking for someone who: Has a PhD degree in any area related to the tasks (e.g. Computer Science, Digital Humanities, or Information
-
research on the topic outlined above is paramount Candidates are expected to be interested in working at the boundaries of several research domains PhD degree in computational biology, bioinformatics
-
researcher with expertise in the area of spiking neural networks and an interest in (applications of) probabilistic computing. The postdoc candidate will participate in the NWO NWA project "Acting under
-
different physico-chemical environments to drive self-organisation processes, like condensates, that shape mesoscale structures enabling tissue function. As a Postdoctoral Researcher at the Rosalind Franklin
-
for interdisciplinary research. The research program of ACER is multidisciplinary, with faculty members from backgrounds in Chemistry, Chemical Engineering, and Environmental Engineering focusing on different research
-
aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
-
skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
-
aims at addressing computational challenges associated with data acquisition and information extraction from complex sensors and sensor networks. Crucially, uncertainty management and quantification