12 computer-science positions at AMOLF

PhD-student: Physical learning machines

ways in which such physical learning is realized, and design new types of learning machines capable of solving complex engineering problems on their own. Some examples include neuromorphic computers

Phd – student: Nonlinear metaphotonics for UV semiconductor metrology

the NWO research programme NanoXUV we will develop nanophotonic structures that convert infrared wavelengths to coherent structured light of very short wavelength, in the UV and even extreme ultraviolet

Two PHD positions: Metasurfaces for energy-efficient wave-based computing

to contribute to new technologies that realize radical improvements in the energy efficiency of information and communication technology? As part of the Dutch consortium NL-ECO on energy-efficient computing

Internship: Machines that design themselves; inventing green nanomechanical systems using large language models

improves through the experimentation process. Qualifications The internship is open to master’s degree candidates from a range of backgrounds, including Engineering, Physics, Computer Science, Mathematics

Two PhD positions: Fano4nano – Fano resonance enhanced scatterometry for wafer metrology

physics and design principles of natural and man-made complex matter, with research in the disciplines nanophotonics, nanophotovoltaics, chemistry & spectroscopy, mechanical metamaterials and biophysics

Postdoc : Shining light on atomic scale processes

to make and stabilize high-index facets and program atomic defects by kinetically trapping non-equilibrium structures by tuning laser excitation conditions. Achieving such atomic control is a long-sought

Internship: Shedding light on fungal carbon transport from image data

Science . Qualifications We are seeking highly motivated students with strong quantitative and computational skills. We are looking for someone comfortable in code development, using git and coding in

Postdoc: Information processing in mycorrhizal mycelial networks

this information to mediate trade over space and time? How can an organism with such a diffuse networked anatomy process information in a coordinated manner? Are there simple computational strategies employed by

PhD-student: Chiral

candidates with a strong background in chemistry, physics, materials science, or engineering with an interest in self-assembly phenomena. Excellent candidates with training in any area of science or

Postdoc: Inverse design of photonic metamaterials through physics-informed deep learning

beyond. For more information, see www.optomechanics.nl . Qualifications We seek an excellent candidate with a background in physics or photonics engineering and relevant experience with machine learning