| Solid programming experience in C or C++ | Experience in hands-on development and troubleshooting | Proven work experience in Software Engineering → Travel the world to help us set-up the systemĪnd make simplified plant production a reality. → Bridge the gap from the sensor to S3 buckets. → Perform first pre-processing steps on the sensor to reduce bandwidth requirementĪnd fully utilize the onboard computing powers. → Help to integrate the sensor into custom automation solutions and drive theĭevelopment of the embedded components to improve imaging speed and Including existing embedded systems (Intel® RealSenseTM + FLIR camera systems). → Design and implement the software to control a spectral sensor, → Take control of our spectral sensor and custom automation projects. Experience of supervising/mentoring students at bachelor, master, or PhD level is a plus.Įxperience of working with computer vision and deep learning toolkits on at least one of the following platforms – Python, C/C++, MATLAB, Keras, PyTorch, Tensor Flowĭemonstration of programming proficiency in at least 2 of the following platforms: Python, MATLAB, OpenCV, Keras/PyTorch/Tensor Flow,etc.Ī successful candidate should have a strong interest in at least one of the following topics: fundamental machine learning, neural network architecture, artificial intelligence, scalable learning, and interpretable learning, artificial intelligence for bioimaging.Įmphasis shall also be attached to personal suitability. Experience of publishing works related to artificial intelligence in top computer science publication venues (CVPR, ECCV, ICCV, NeurIPS, ICML, ICLR, IEEE TIP, IEEE TPAMI, IEEE TCI, IEEE TMI) is preferred. Candidate should have a publication and open source code profile related to these topics. The candidate must have had experience with developing, customizing, and applying modern deep learning architecture. This position requires a PhD degree or equivalent in Computer Science, Mathematics, Computing, or Engineering in topics related to artificial intelligence. Agarwal, “Physics-Guided Loss Functions Improve Deep Learning Performance in Inverse Scattering,” IEEE Transactions on Computational Imaging, 8, 236-245, 2022. Prasad, “Physics-based machine learning for subcellular segmentation in living cells” Nature Machine Intelligence, 3(12), 1071-1080, 2021. Prasad, “Learning nanoscale motion patterns of vesicles in living cells,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Washington, USA, 14-19 June, 2020. A compulsory contribution of 2% to the Norwegian Public Service Pension Fund will be deducted. At present gross salary for postdoctoral fellow starts at NOK 553,100 per annum. Salary: The remuneration for Postdoctoral research fellow is in accordance with the State salary scale code 1352. Location: UiT The Arctic University of Norway, Tromsø, Norway The candidate will have opportunity to work across two teams – Bio-AI Lab ( ) and 3Dnanosopy group ( ) which are both funded through several prestigious EU and Research Council of Norway projects.ĭuration: The normal period of appointment is three years. The position offers a unique opportunity of developing career in a highly multidisciplinary (artificial intelligence, physics/optics, life science, computational modeling) cutting edge research arena with a potential to create high impact. The position entails developing machine learning models towards interpretable and scalable artificial intelligence, and with life science interpretations from 2D/3D microscopy (fluorescently-labeled and label-free) image and video data of biological samples as the target application area. The position being announced here relates to Physics-based Artificial Intelligence.
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