Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- Aalborg University
- Aarhus University
- Aalborg Universitet
- University of Copenhagen
- Aarhus University (AU)
- Technical University of Denmark (DTU)
- Copenhagen Business School
- Technical University of Denmark;
- TEGNOLOGY APS
- Technical University Of Denmark
- Technical University of Denmark
- University of Southern Denmark (SDU)
- 2 more »
- « less
-
Field
-
by the Carlsberg Foundation. SMARTbiomed is a research center with core mission to develop statistical and computational methods focusing on causal inference, risk prediction and machine learning
-
, cryo-electron microscopy (cryo-EM), cryo-EM-based polyclonal serology (cryo-EMPEM), molecular dynamics simulations, machine learning, and structural biology to define epitopes and engineer improved
-
such as Google Earth Engine statistical modelling, machine learning, cloud/high-performance computing retrieving ecologically relevant environmental data from national to global databases research and/or
-
engineering, system integration, electrical engineering, machine elements, robotics, sensors, mechatronics, and advanced actuator design. As associate or full professor, you are expected to contribute
-
-experiment using advanced battery cycling machines, chambers, battery emulators, BMS-in-the-Loop, etc.) Ability to work and lead multidisciplinary research teams involving applied AI, digital twins, and
-
., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) may be involved. Training will be provided in all methodologies but prior experience with some
-
DTU Tenure Track Assistant Professor in Surface Physics and Catalysis for Sustainable Energy Solu...
, robotics, digital twins, and machine learning, CAPeX is redefining how new P2X materials are discovered and developed. Commitment to Diversity We value diversity and encourage applications from individuals
-
machines Conduct simulations and experimental testing to validate system performance Document and disseminate research results through scientific publications and presentations The PhD candidate will work
-
, and machine-learned force fields to describe ion transport and interfacial evolution. These models will be extended to mesoscopic and continuum scales (kinetic Monte Carlo, phase-field) to capture
-
quantitative analysis of register, survey, and patent data to various qualitative methods. If you have an interest in, or experience with, novel computational methods such as NLP, machine learning, and AI