Sort by
Refine Your Search
-
such as autonomous cars and robots. Job description We have multiple open PhD positions at AVI@PRS and we are looking for motivated candidates with a strong background in computer vision, machine learning
-
are also expected. Profile PhD in Data Science, Computer Science, Mechatronics, Remote Sensing, Engineering Geology or other related discipline Demonstrated expertise in machine learning and computer vision
-
, access state-of-the-art computational resources, and contribute to high-impact research that bridges academia and industry. If you have a strong background in AI, machine learning, and a keen interest in
-
these projects will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The two doctoral student positions
-
of circularly polarized / chiral phonons in quantum paraelectric materials. Job description The postdoctoral researcher will develop machine-learned force fields trained on density functional theory (DFT) outputs
-
and Machine Learning (ML). By enriching datasets and leveraging advanced simulations to optimize ML models, we seek to enhance manufacturing efficiency and quality control in casting processes. Job
-
degree in Computer Science, Data Science, or a related technical field with strong foundations in machine learning OR Master's degree in Mathematics, Statistics, Physics, or other quantitative discipline
-
argon liquid phase using electronic structure calculations. Developing computer code for computing ionization rates with general dark matter-electron interactions. Exploring appropriate descriptions
-
or using company-level data. We are looking for candidates with expertise in either Smart Manufacturing and/or Operational Excellence: Smart Manufacturing covers the application of digitalization, machine
-
partners. You will have the unique opportunity to learn, develop and apply a range of cutting-edge modeling and computational techniques. You will also be exposed to experimental methods used to produce data