11 machine-learning-phd positions at KTH Royal Institute of Technology in Sweden

Phd students in System Security, Formal Verification and Machine Learning

with a strong background in system security, formal verification, and/or machine learning to apply for two PhD positions, funded by Wallenberg AI, Autonomous Systems and Software Program (WASP

Postdoc in under-supervised deep learning

. This eligibility requirement must be met no later than the time the employment decision is made. Prior publications within top machine learning venues. Prior experience with under supervised deep learning during PhD

PhD student within Multi-Modal Modeling of Spatial Biology Data

on machine learning systems in PyTorch or JAX have experience in interpretable methods in machine learning have experience in using version control systems like Git and public repositories like GitHub

Doctoral students in Robotics and machine learning

the sense of smell works in humans and build AI models of these. We seek a candidate who have experience working with time series data (EEG), signal processing and machine learning. PhD student 2 will work

Postdoc in biomedical and experimental fluid mechanics

of Mechanics we focus on blood flow phenomena, blood clot formation and bleeding due to artificial life-supporting devices such as heart-and lung machines and heart support pumps, but also on formation

Doctoral student in Human Computer-Interaction

an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Human-Computer Interaction Inclusive Digital Learning

Doctoral student in Programming Languages and Machine Learning

Communication Technology The doctoral student position focuses on fundamental research combining programming languages theory, compilers, and machine learning. In particular, the emphasis is on algorithms, formal

Postdoc in Biophysics

culture, isolation of cells from blood and tissue. Experience of image analysis, machine learning or related fields. Practical experience of programming. An interest in multi-disciplinary research

Doctoral student in data-driven methods for organizing healthcare

Preferred qualifications Strong programming skills in Python, and other relevant languages (such as R) Background in AI, machine learning, data science, statistics, preferably with a focus on both statistical

Doctoral student in Spatial Proteomics

to the understanding of the protein dynamics on a single cell level. You will collaborate with other research groups that develop complementary spatial omics methods and machine learning approaches to model spatial