The Friedrich Miescher Institute (FMI) in Basel (Switzerland) seeks an enthusiastic and highly motivated individual with a strong vision to establish and drive the development of machine learning tools for segmentation and analysis of biomedical image data. The FMI is a world-leading research institute focusing on fundamental biological questions with strong medical relevance. The position will initially be for two years with perspective for long-term employment.
The candidate will be responsible for the development and application of machine learning toolboxes, in particular deep convolutional networks, for the analysis of a broad spectrum of image data. Research groups at FMI use a variety of different imaging methods to address questions in cell biology, genetics, neurobiology, and other disciplines. The candidate will collaborate closely with the Facility for Advanced Imaging and Microscopy (FAIM) and will be supported by the IT group for high-performance computing.
We are looking for a highly motivated and skilled individual with expertise in machine learning and computer vision. The candidate has a thorough training in the use and development of machine learning tools including deep convolutional networks. Experience with toolboxes such as TensorFlow, Caffe and Torch, as well as a Bachelors/Masters degree in physics, applied mathematics, computer science or an appropriate engineering discipline are expected. Experience in microscopy, and cell and tissue imaging, possibly through a PhD, is appreciated.
The candidate should have excellent communication and networking skills. He/she should be able to organize tasks in a dynamic social environment and enjoy interacting with a diverse group of researchers in quantitative cell biology and image-based data analysis.