Focus on:- developing unique combinations of Deep Learning and classical algorithms to solve complex computer vision tasks for real-world problems, such as: * automatic digitization of centuries-old hand-drawn mining plans into 3D models * automatic quality assurance for machine production processes- developing AI-based time series forecasting algorithms for green energy transition purposes- developing optimisation algorithms - strong experience in python… Show more Focus on:- developing unique combinations of Deep Learning and classical algorithms to solve complex computer vision tasks for real-world problems, such as: * automatic digitization of centuries-old hand-drawn mining plans into 3D models * automatic quality assurance for machine production processes- developing AI-based time series forecasting algorithms for green energy transition purposes- developing optimisation algorithms - strong experience in python and associated deep learning libraries such as e.g. tensorflow - successful representation of OmegaLambdaTec at hackathons and international conferences Show less

As an astroparticle physicist, I am an active member of the highly competitive field of multi-messenger physics and astronomy. I am working as part of a team of local experts in Munich as well as two international collaborations, IceCube and P-ONE. Besides numerous technical tasks and regular teaching activities, the main part of my work consists of the preparation, statistical analysis, and interpretation of experimentally measured data. These tasks include:* Development… Show more As an astroparticle physicist, I am an active member of the highly competitive field of multi-messenger physics and astronomy. I am working as part of a team of local experts in Munich as well as two international collaborations, IceCube and P-ONE. Besides numerous technical tasks and regular teaching activities, the main part of my work consists of the preparation, statistical analysis, and interpretation of experimentally measured data. These tasks include:* Development, implementation, optimization, and testing of several high-level statistical methods to find the sources of astrophysical neutrinos. This includes advanced experience with maximum likelihood fits, likelihood ratio tests, Frequentist statistics, Bayesian statistics, minimization algorithms, fitting algorithms, etc.* Development of the required software libraries.* Implementation, optimization, vectorization, and parallelization of statistical software frameworks in Python and C++.* Data fitting and illustration. Besides many classical fitting approaches, this includes experience with regression algorithms and kernel density estimation methods.* Processing and filtering of large data sets. This includes experience with big data, machine learning methods such as boosted decision trees, etc.* Reconstruction of distinct properties appearing in the data. This includes experience with simple least square minimization, maximum likelihood algorithms as well as deep learning methods.* Experience with version control systems, shell scripting, and HTC computing with HTC Condor.* Membership and participation in two international and scientific collaborations.* Regular presentation of my individual progress as well as results from team efforts from our group at several national and international conferences.* High demands on an independent work attitude as well as working in teams Show less

As part of a team in Munich, I was supporting the design and construction of a tracking detector used in the COMPASS experiment located at CERN.