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Student Theses and Jobs

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We always have open topics for Bachelor and Master Theses, Forschungspraktika, Hochschulpraktika and Master Projects and also open positions for student work (HiWi positions). You can find most of them listed in the tables below. If you do not find a suitable topic in there we would still like to encourage you to contact us and tell us about your ideas.

Please use the contact form below to apply for any of the listed topics, open positions or to propose your own topic. We will then get in contact with you.

Open Research Topics

[B] = More suited for a Bachelor’s Thesis
[M] = More suited for a Master’s Thesis
[P] = More suited for Project (e.g. Computer Science “Master Project”)
[I] = More suited for a Implementation Task
[RI] = More suited for Research Internship

Thesis ID Scope Topic Area Supervisor
1927 RI/P StereoViper – 3D stimuli for assessment and training of stereoacuity HCI, Computer Graphics Wolfgang Mehringer (M. Sc.)
2003 P/RI Assessing the Effect of Neurofeedback based Training in Virtual Reality HCI Markus Wirth (M. Sc.)
2012 M Digital phenotyping of chronic pain patients undergoing neuromodulation
(in cooperation with the Medical Faculty, Neurosurgery)
Data Analysis,
Machine Learning,
Biomedical Signal Analysis
Dr.-Ing. Felix Kluge
Prof. Dr. med. Thomas M. Kinfe
2014 M/P/RI Approximation of physical based LIDAR simulation in Blensor using Deep Learning Machine Learning, Simulation Franz Köferl (M. Sc.)
2020 B/M/P/RI Investigation of a Blockchain-based service network for digitalisation of the maternity log (Mutterpass) in the German healthcare system. Focus is on consumer-to-(healthcare-)provider transactions and verifications and anonymous information storage of the maternity log contents on the Blockchain using smart contracts. Digital Health Stefan Gradl (M. Sc.)
Michael Nissen (M. Sc.)
Dr. rer. nat. Hanna Hübner (Frauenklinik, UK Erlangen)
2023 RI/P/M “Mixed-Type and Irregularly Sampled Time Series Analysis” – Such data includes for example electronic health records (EHR) or combined sensor and event log data. Tasks include the extension of RNN architectures to deal with such data efficiently. Deep Learning, Machine Learning, Time Series Analysis An Nguyen (M. Sc.)

Leo Schwinn (M. Sc.)

2027 P/RI Requirements Engineering and Market Research for Pregnancy and Maternity Mobile Apps Digital Health Michael Nissen (M. Sc.)
Stefan Gradl (M. Sc.)
Dr. rer. nat. Hanna Hübner (Frauenklinik, UK Erlangen)
2028 P/RI Implementing a reference algorithm for anomaly segmentation using the MVTec AD dataset Machine Learning, Deep Learning Franz Köferl (M. Sc.)
2030 M Classification of localized defects on silicon carbide (SiC) wafers using domain adaptation techniques Deep Learning, Transfer Learning, Domain Adaptation Matthias Zürl (M. Sc.),
Franz Köferl (M. Sc.),
Intego GmbH
2033 M Clustering of disease trajectories and prediction of outcomes from large real-world datasets Digital Health, Machine Learning Novartis Institutes for Biomedical Research Translational Medicine
2034 P/RI SMART Start: Digitising and improving prenatal and maternal care through the use of wearables and machine learning Digital Health, Machine Learning Michael Nissen (M. Sc.)
Stefan Gradl (M. Sc.)
Dr. rer. nat. Hanna Hübner (Frauenklinik, UK Erlangen)
2035 B/M Machine learning for systems biology – Molecular profiling of IBD patients for prediction and monitoring of response to targeted therapies Digital Health,
Machine Learning,
Systems Biology
Prof. Dr. Björn Eskofier
Prof. Dr. Raja Atreya
(UK Erlangen)
2039 RI Adaptation of existing sit-to-stand transition detection algorithms to a new sensor position for real-time vertigo analysis Motion Analysis,
Digital Health,
Signal Processing,
Machine Learning
Robert Richer (M. Sc.)
2041 M Towards Training Robust Neural Networks: On the Effect of Regularizing Attacks During Adversarial Training Adversarial Machine Learning, Deep Learning Leo Schwinn (M. Sc.)

René Raab (M. Sc.)

2043 RI Automatic detection and correction of sensor orientation in wearable gait analysis Gait Analysis, Signal Processing Martin Ullrich (M. Sc.)
Malte Ollenschläger (M. Sc.)
Arne Küderle (M. Sc.)
 2044 RI User experience and acceptance evaluation of a digital maternity-log (Mutterpass) application as well as wearable and smart devices in the context of home-use HCI, Digital Health Katharina Jäger (M. Sc.)

Stefan Gradl (M. Sc.)
Michael Nissen (M. Sc.)
Dr. rer. nat. Hanna Hübner (Frauenklinik, UK Erlangen)

2046 M Adversarial Robustness through Saliency-based Noise Injection Adversarial Machine Learning, Saliency, Deep Learning Leo Schwinn (M. Sc.)

Dr. Dario Zanca

2047 RI Activity Recognition using IMU sensors integrated into Hearing Aids.
Implementation and evaluation of an activity recognition algorithm.
Machine Learning, Signal Processing Ann-Kristin Seifer (M. Sc.)
2101 B/M Prediction of MRI Patient Experience, Physiological Stress, and Behavioral Outcomes from Psychological Variables
(in collaboration with Chair of Health Psychology and Siemens Healthineers)
Machine Learning,
Health Psychology
Robert Richer (M. Sc.),
Janika Madl (M. Sc.),
Prof. Dr. Nicolas Rohleder
2102 P/RI Artificial Intelligence trends in healthcare – Evaluation and application of topic clustering methods using podcast data Data Analysis, Machine Learning Philipp Dumbach (M. Sc.)
Leo Schwinn (M. Sc.)

Student Assistant Jobs

Job ID Topic Area Supervisor
2002 Deep Learning/Machine Learning for Mixed-Type and Irregularly Sampled Time Series Analysis  (focus on fundamentals) Deep Learning, Machine Learning, Time Series Analysis An Nguyen (M. Sc.)

Dr. Dario Zanca

2003 Deep Learning for Adversarial Robustness Deep Learning, Adversarial Robustness Leo Schwinn (M. Sc.)

René Raab (M. Sc.)

2004 Teaching assistant for the course “Machine Learning for Engineers” Machine Learning Franz Köferl (M. Sc.)

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    What are you currently studying (e.g. "Master Medizintechnik")?

    What kind of work are you interested in? (*)
    Bachelor's ThesisMaster's ThesisStudent work (HiWi)ForschungspraktikumHochschulpraktikumMaster's Project (Computer Science)

    When would you ideally want to start? (*)

    In the following you can tell us your interest in a specific topic or in the general research area. If you have a brilliant idea and want to generate a new topic, please select our area of research that is most fitting, and describe your idea in two sentences.