13 process-optimization Postdoctoral positions at Chalmers University of Technology in Sweden
Sort by
Refine Your Search
-
graphene-based field effect transistor sensors with biological receptors for infection biomarkers, and optimize this technology for diagnosing infections in the wound settings. As a postdoctoral researcher
-
analysis Ship resistance and motions Propulsion systems and energy efficiency Activities range from basic science—advancing understanding of the physics that govern ship design and operation—to applied
-
Do you dream of organic and holistic ways of automating the design, motion optimization and control of legged robots? With this postdoc position, you have the opportunity to be a part of the ongoing
-
apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
-
Integrated photonics is a vibrant research field dealing with the generation, processing, and detection of light at the chip scale. Inverse design, the computer-aided automatic design of photonic devices
-
which marine microalgae-based technologies are used to upcycle nutrients from saline seafood process waters, while simultaneously producing valuable biomass. A core of the project is to tailor mild
-
to pioneering research aimed at developing a comprehensive framework for the integrated and coordinated operation of conventional and converter-based energy resources across diverse grid scenarios. The ultimate
-
to upcycle nutrients from saline seafood process waters, while simultaneously producing valuable biomass. A core of the project is to tailor mild biorefinery sequences to the microalgal biomasses for recovery
-
are looking for a curious and driven postdoctoral researcher to join a project focused on improving how we study and optimize medical treatments. The work centers on advancing a vessel-on-a-chip platform—a
-
algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite