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| == General procedure == After the supervisor has been found (see below), the student must write a proposal that includes the research question and its context/motivation, related work, '''preliminary''' methodological and/or experimental results, and formalities such as time constraints. After Prof. Müller approves the proposal, the student can register the thesis, and the writing period begins (typically three months for BA and six months for MA). This implies that a thesis often requires more time than the official writing period. It might be possible to hand in the thesis early (check with the respective examination regulations for the student’s degree program). However, we encourage significant time between registration and submission. |
== Finding a supervisor == Interested students can contact a group member listed below with our [[https://www.dropbox.com/s/qcx71xtx6a0vw4u/thesis_request_form.docx?dl=0|thesis request form]], a curriculum vitae/resume, and an optional cover letter. Prior knowledge of machine learning is mandatory, e.g., as acquired through the courses offered by our group. Many theses are connected to ongoing research in our group. However, it is also possible for students to suggest own topics/ideas. |
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| == Finding a supervisor == Interested students should provide a curriculum vitae/resume. Among other relevant aspects, this document should inform about the grades in relevant modules. Prior knowledge of machine learning is mandatory, e.g., as acquired through the courses offered by our group. Students should also describe their research interests/ideas, including '''suitable and proven''' skills, e.g., in Python programming, mathematics, or scientific writing. Optionally, it is possible to suggest own topics. Our senior researchers can identify suitable internally advertised topics or suggest suitable supervisors within our group: |
Our senior researchers can either supervise directly or suggest internally advertised topics and suitable supervisors: |
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| * Explainable AI & Natural Language Processing: Oliver Eberle (oliver.eberle@tu-berlin.de) | |
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| * Robustness against spurious correlations in DNNs, neural cellular automata: Lorenz Linhardt (l.linhardt@campus.tu-berlin.de) * Combining Explainable AI & Deep Generative Models like Diffusion Models, Large Language Models, GANs, VAEs and Normalizing Flows in different modalities: Sidney Bender (s.bender@tu-berlin.de) |
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| You can find further information about our group members, including their research, on [[https://doc.ml.tu-berlin.de/publications/|our group's publication list]] and the [[https://www.bifold.berlin/research/people|BIFOLD website]]. | You can find further information about our group members on [[https://doc.ml.tu-berlin.de/publications/|our group's publication list]] and the [[https://www.bifold.berlin/research/people|BIFOLD website]]. |
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| === Open topics === '''Our [[https://wiki.ml.tu-berlin.de/wiki/IDA/ThesisTopicsNewInternal|internal wiki]] contains additional open topics. The group members listed above can match interested students with internally advertised topics.''' |
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| == Open topics == Group members can find open topics in our [[https://wiki.ml.tu-berlin.de/wiki/IDA/ThesisTopicsNewInternal|internal wiki]]. |
|| '''MS/BS''' || '''Topic''' || '''Supervisor + email address''' || '''Date of entry''' || '''Additional information'' || || - || - || -|| - || - || == General procedure == After having found a supervisor, students prepare a proposal that includes * the research question and its context/motivation, * related work, * preliminary methodological and/or experimental results, * and formalities such as the number of ECTS credits and the writing time as specified in the student’s examination regulations. The supervisor can help the student with writing the proposal. Students can register the thesis with the examination office after Prof. Müller approves the proposal. We encourage students not to underestimate the time required for writing the proposal. Furthermore, consider that we may require some time to review the proposal. Therefore, it is helpful to contact our group early. |
Master and Bachelor Thesis Supervision (public landing page)
Finding a supervisor
Interested students can contact a group member listed below with our thesis request form, a curriculum vitae/resume, and an optional cover letter. Prior knowledge of machine learning is mandatory, e.g., as acquired through the courses offered by our group. Many theses are connected to ongoing research in our group. However, it is also possible for students to suggest own topics/ideas.
Though our group tries to supervise as many students as possible, we typically do not have the capacity to supervise every interested student.
Our senior researchers can either supervise directly or suggest internally advertised topics and suitable supervisors:
ML for Quantum Chemistry: Stefan Chmiela (stefan@chmiela.com)
Kernel Learning: Stefan Chmiela (stefan@chmiela.com)
Explainable AI: Grégoire Montavon (gregoire.montavon@tu-berlin.de)
Anomaly detection/Unsupervised learning: Robert Vandermeulen (vandermeulen@tu-berlin.de)
Probabilistic modeling and inference: Shinichi Nakajima (nakajima@tu-berlin.de)
Time series analysis and signal processing: Andreas Ziehe (andreas.ziehe@tu-berlin.de)
Multimodal signal acquisition and analysis - neurotechnology + biomedical sensing: Alexander von Lühmann (vonluehmann@tu-berlin.de)
ML for Security & Privacy: Daniel Arp (d.arp@tu-berlin.de)
Explainable AI & Natural Language Processing: Oliver Eberle (oliver.eberle@tu-berlin.de)
Alternatively, it is possible to contact junior researchers directly with specific ideas or inquiries:
- Learning with multiple modalities: Jannik Wolff (wolff [dot] jannik [at] icloud.com)
Robustness against spurious correlations in DNNs, neural cellular automata: Lorenz Linhardt (l.linhardt@campus.tu-berlin.de)
Combining Explainable AI & Deep Generative Models like Diffusion Models, Large Language Models, GANs, VAEs and Normalizing Flows in different modalities: Sidney Bender (s.bender@tu-berlin.de)
You can find further information about our group members on our group's publication list and the BIFOLD website.
Open topics
Our internal wiki contains additional open topics. The group members listed above can match interested students with internally advertised topics.
MS/BS |
Topic |
Supervisor + email address |
Date of entry |
Additional information |
- |
- |
- |
- |
- |
General procedure
After having found a supervisor, students prepare a proposal that includes
- the research question and its context/motivation,
- related work,
- preliminary methodological and/or experimental results,
- and formalities such as the number of ECTS credits and the writing time as specified in the student’s examination regulations.
The supervisor can help the student with writing the proposal. Students can register the thesis with the examination office after Prof. Müller approves the proposal. We encourage students not to underestimate the time required for writing the proposal. Furthermore, consider that we may require some time to review the proposal. Therefore, it is helpful to contact our group early.