Open positions

Currently there are several positions to be filled.

Research Associate (m/w/d, E13 TV-L, 100%)

The University of Tübingen invites applications for the position of a

Research Associate (m/w/d, E13 TV-L, 100%)

starting July 1, 2021. The position is limited to 31.12.2025.

In the context of the Cluster of Excellence "Machine Learning: New Perspectives for Science", funded through the Excellence Strategy of the German Federal and State Governments, the Cloud Infrastructure at the University of Tübingen is being expanded.

The planned work is aimed at the expansion and operation of the ML Cloud (https://uni-tuebingen.de/en/199372) that has extensive CPU and GPU compute-capacities as well as a storage volume in the petabytes. The close collaborative partnership with the relevant scientific working groups is essential to be able to depict their workflows in the ML Cloud in a technically appropriate manner. Aside from research activities for the expansion and development of the ML Cloud, further responsibilities include supporting and further developing of the corresponding training program for users.

Candidates are expected to have knowledge about the basics of data management, to work scientifically independent, to be able to professionally interact with heterogenous user groups, to be flexible, to be able to work in a team and to have a good command of English. In addition, knowledge of cloud computing and virtualization as well as experience in operating complex IT-infrastructures and an interest in modern technologies are desirable. Didactic skills or experience in training scientists are also an advantage.

The university seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. 

Applications with the usual documents should be sent in electronic form to the Central Office of the Cluster of Excellence "Machine Learning - New Perspectives for Science" (ml-in-sciencespam prevention@uni-tuebingen.de) by May 15, 2021. Questions can be directed to Dr. Jens Krüger (jens.kruegerspam prevention@uni-tuebingen.de). The employment will be carried out by the central administration of the University of Tübingen.

PhD Position (m/f/d; E13 TV-L, 80%) in Compositional Data Synthesis

The Bosch Industry-on-Campus Lab, a research collaboration between the University of Tübingen and Bosch Center for AI (BCAI), invites applications for an open

PhD position (m/f/d; E13 TV-L, 80%)

in Compositional Data Synthesis. The aim of this project is to learn how to synthesize new, previously unseen visual scenes through object compositionality. A bias to account for the compositional way in which humans structure a visual scene in terms of objects has frequently been overlooked. In this project, you will investigate object compositionality as an inductive bias for deep generative models, such as generative adversarial networks (GANs). Specifically, you will focus on how to generate novel unseen compositions of objects present in the training set.

You will be jointly supervised by Prof. Dr. Zeynep Akata from the University of Tübingen side (Cluster of Excellence 'Machine Learning') and Dr. Anna Khoreva from the Bosch side.

The position is available immediately (but start date is negotiable), the contract is initially for three years, and remunerated according to the German salary scale 13 TVL.

What are you going to do?

As part of the Bosch Industry-on-Campus Lab at the University of Tübingen, you are going to carry out AI research and develop novel deep generative models, learning to synthesize new data samples through the notion of compositionality. There will also be regular visits and interactions with researchers at Bosch Center for AI, who have an office on campus. At the University of Tübingen you will be supervised by Prof. Dr. Zeynep Akata and Dr. Anna Khoreva.

Your tasks will be to:
  • Develop new computer vision and/or deep machine learning methods on compositional data synthesis;
  • Collaborate with other researchers within the lab and BCAI Research;
  • Complete and defend a PhD thesis within the official appointment duration of three years;
  • Regularly present internally on your progress and help Bosch write patent applications to protect inventions from the lab when requested.
  • Regularly present intermediate research results at international conferences and workshops, and publish them in proceedings and journals;
  • Potentially assist in relevant teaching activities.
What do we require?
  • Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or related field;
  • Strong background in computer vision and/or machine learning;
  • Excellent programming skills, preferably in Python;
  • Prior experience of working with deep learning libraries, such as PyTorch or TensorFlow;
  • Solid mathematics foundations, especially in probability theory, statistics, calculus and linear algebra;
  • High motivation and creativity;
  • Strong communication, presentation and writing skills and excellent command of English.

Prior publications in relevant vision and machine learning venues as well as experience working with deep generative models (e.g. VAEs, GANs, Flows) will be advantageous for your application.

Application

The University of Tübingen is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We seek to increase diversity and the number of women in areas where they are under-represented and therefore explicitly encourage women to apply. We are also committed to recruiting more people living with disabilities and strongly encourage them to apply. The employment will be carried out by the central administration of the University of Tübingen.

Do you recognize yourself in the job profile? Then we look forward to receiving your application by May 31st, 2021. Please note the position will be filled as soon as an appropriate candidate is found. 

Your application should consist of a single PDF file <lastname_firstname>.pdf containing:

  • A two-page motivational letter, which: 1) explains why you would like to join us and 2) describes the research topics that excite you and that you would like to pursue in your PhD;
  • Your CV, with details of publications and conference participations (if applicable);
  • A copy of your Master’s degree certificate, if you already have one;
  • Unofficial transcripts of all of your university studies (BSc and MSc), as well as a translation into English and explanation of grading system (if needed);
  • Letters of recommendation and/or contact details of 2-3 referees;
  • Link to github or enclosed code sample you have written;
  • Optionally, additional documents such as a thesis, published papers, or project portfolios.

You may apply by sending your documents to eml-sekretariatspam prevention@inf.uni-tuebingen.de.

PhD position (m/f/d; E13 TV-L, 65%) Human and Machine Cognition

The “Human and Machine Cognition” lab of the Cluster of Excellence “Machine Learning: New Perspectives for Science” and the “Tübingen AI Center” invites applications for an open

PhD position (m/f/d; E13 TV-L, 65%)

to be filled as soon as possible. The position is limited to three years.

About the group:

The HMC lab is led by Dr. Charley M. Wu and operates at the intersection of Human Cognitive Science and Machine Learning research. The focus of this position will be to study the strategies that humans use to learn from and interact with other people in social settings. Potential topics include the integration of social and individual information, computationally tractable implementations of Theory of Mind inference, and cumulative cultural evolution in online communities, in addition to the interests of the candidate.

Members of the lab are working on a diverse set of topics including, structure learning in planning and search, developmental changes in learning and exploration, inductive biases in compositional learning, and many more. Our research methods include online experiments (commonly in the form of interactive games), lab-based virtual reality experiments, computational modeling of behavior, evolutionary simulations, developmental studies (comparing children and adults), fMRI/EEG, and analyzing large scale real-world datasets. We have a rich collaboration network of researchers from Harvard, Princeton, UCL, and several Max Planck Institutes around Germany. To find out more, visit the lab website at www.hmc-lab.com.

About the position:

The candidate should hold a MSc degree in cognitive science, computer science, psychology, computational neuroscience, statistics, or any relevant discipline. The ideal candidate should be self-motivated, comfortable with both analytic and critical thinking, and have a passion for science. Please indicate in your application if you have prior experience with conducting experiments, computational modeling, machine learning, and/or neuroimaging (EEG/fMRI). Skills in computer programing languages (e.g., R, Python, Matlab, Javascript, Java, etc.), mathematics, writing (in English), and the ability to independently manage a project (of any type) should also be mentioned.

About Tübingen:

Tübingen is a scenic university town on the Neckar river in South-Western Germany. The quality of life is exceptionally high and the atmosphere is diverse, inclusive, and most locals speak English. Tübingen offers excellent research opportunities due to the University, four Max Planck institutes, the University Hospital, and Europe’s largest AI research consortium. You can find out more about Tübingen here: https://www.tuebingen.de/en/

How to apply:

Please send a cover letter, a description of your research interests (max 1 page), your CV, the names and email addresses of 2-3 referees, and unofficial copies of your University degrees to Charley Wu (charley.wu@uni-tuebingen[dot]de). If you have any questions about the position, please do not hesitate to contact Charley directly. The university seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of Tübingen. Please submit your application by May 15th, 2021.

PhD position (m/f/d; E13 TV-L, 65%) in machine learning in climate science

The Machine Learning in Climate Science research group at the Cluster of Excellence “Machine Learning,” University of Tübingen, invites applications for a

PhD position (m/f/d; E13 TV-L, 65%)

to develop seasonal forecasts of extreme rainfall events over Germany and western Europe using spatiotemporal artificial neural networks (STANNs). The position is funded for three years starting no later than 1 September 2021 and, along with three other PhD projects, is part of the mini-graduate school Modeling and Understanding SpatioTemporal Environmental INteractions (MUSTEIN).

MUSTEIN aims at developing machine learning (ML) techniques that reliably learn explainable models of critical aspects of four highly interacting spheres, focusing on (i) seasonal weather dynamics (P1), (ii) river water discharge (P2), (iii) soil erosion (P3), and (iv) solar thermal systems (P4). The targeted ML-based systems will potentially allow us to (i) predict environmental system dynamics more accurately and for longer periods into the future, (ii) anticipate future climatic developments and prepare accordingly, (iii) partially control the developments, and (iv) explain the hidden causes and influences in an accessible, causal manner.

Qualifications

You should hold a MSc degree (or should have one by June 2021) in computer science, physics, mathematics, statistics, geoscience, earth science, meteorology, or any other relevant discipline. A background in probability and statistics, along with a basic knowledge of artificial neural networks and deep learning is preferable. You should be capable of independent, creative, and critical thinking, and you should be willing to tackle challenging problems which do not offer easy resolutions at first sight. Ideally, should you have experience in scientific programming, along with some prior experience of working with deep learning libraries such as PyTorch or TensorFlow. If you have prior research experience, such as from a Master’s thesis project or in the form of a conference paper or a manuscript, it will add significantly to the strength of your application.

Role

You will work towards a PhD degree, to be completed within three years from the start of funding. You will conduct supervised scientific research within Project P1: Seasonal Weather Forecast of MUSTEIN. This will involve developing new methods and techniques to analyse extreme rainfall over western Europe using STANNs and to develop a probabilistic seasonal forecast scheme that can be used to anticipate the frequency of extreme rainfall events up to six months in advance. The project will necessitate the analysis of large-scale spatiotemporal climate data sets and the application of state-of-the-art deep learning methods. You will be required to regularly communicate your scientific progress in the form of conference presentations and academic journal articles. Your project will be supervised by Dr. Bedartha Goswami (Machine Learning in Climate Science), in collaboration with Prof. Dr. Martin V. Butz (Neuro-Cognitive Modeling Group), Prof. Dr. Hendrik Lensch (Computer Graphics), and Dr. Nicole Ludwig (Machine Learning in Sustainable Energy Systems). You will take active part in joint research activities with these research groups and also others that are involved in MUSTEIN.

Tübingen

Tübingen is a picturesque town home to one of Germany’s oldest universities dating back to 1477. It also houses four Max Planck Institutes, four Helmholtz Research Centres, three institutes of the Leibniz Association, the University Hospital, and a significant portion of the Cyber Valley initiative, Europe’s largest AI research consortium. The town has a dynamic and intellectually stimulating atmosphere that will allow you to grow as a researcher and as a person. The people here are welcoming, diverse, and inclusive, and most locals speak English. Theater, concerts, exhibitions, and festivals are a regular feature in the town’s calendar and there are numerous possibilities of going out on nature excursions in the surrounding Swabian Jura.

Application

Your application should consist of a single PDF file <lastname_firstname>.pdf containing:

  • a cover letter, explaining why you would like to join us,
  • a statement of research interests (max 2 pages), briefly outlining the research topics that excite you and that you would like to pursue in your PhD,
  • your CV, with details of publications and conference participations (if applicable),
  • a copy of your Master’s degree certificate, if you already have one,
  • a copy of your academic transcripts from your Master’s degree program, and
  • two letters of reference.

Barring the degree certificate, transcripts, and letters of reference, the document should be typeset using left-aligned Times New Roman, Arial, or Calibri typefaces, 12pt font size, single line spacing, and 1 inch margins.

Please send in the application file to Dr. Bedartha Goswami at bedartha.goswamispam prevention@uni-tuebingen.de by 15 May 2021. Shortlisted candidates will be informed by the end of May and interviews will be held virtually in the first week of June. We expect you to start in August preferably, but no later than 1 September 2021.

Equal opportunities

The university seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of Tübingen.

PhD Student or Postdoctoral Researcher (E13 TV-L) in 'Deep learning for studying population codes in the human brain'

 

The Chair for 'Machine Learning in Science' (Prof. Dr. Jakob Macke) in the Cluster of Excellence 'Machine Learning – New Perspectives for Science' and in the Department of Computer Science at Eberhard Karls University Tübingen is currently looking for a


 

PhD Student or Postdoctoral Researcher (E13 TV-L, m/f/d) in 'Deep learning for studying population codes in the human brain'

starting as soon as possible. The initial fixed-term contract will be for 3 years with possible extension.

How do neural circuits in the human brain recognize objects, persons and actions from complex visual stimuli? To address these questions, we will develop deep convolutional neural networks for modelling how neurons in high-level human brain areas respond to complex visual information. We will make use of a unique dataset of neurophysiological recordings of single-unit activity and field potentials recorded from the medial temporal lobe of epilepsy patients. Our tools will open up avenues for a range of new investigations in cognitive and clinical neuroscience, and may inspire new artificial vision systems.  

The position is part of the BMBF-funded project DeepHumanVision in collaboration with the 'Dynamic Vision and Learning' Group at TU Munich (Prof. Dr. Laura Leal-Taixé) and the Cognitive and Clinical Neurophysiology Group at University Hospital Bonn (Prof. Dr. Dr. Mormann).  

Our group develop computational methods that help scientists interpret empirical data, with a focus on basic and clinical neuroscience research. We want to understand how neuronal networks in the brain process sensory information and control intelligent behaviour, and use this knowledge to develop methods for the diagnosis and therapy of neuronal dysfunction.  We aim to work in an interdisciplinary, collaborative and supportive work environment which emphasizes diversity and inclusion.

Tübingen has an internationally renowned research community in artificial intelligence, machine learning and computational neuroscience, including the Cyber Valley Initiative, the Tübingen AI Center, the Excellence Cluster Machine Learning, and the new MSc Program Machine Learning. We are situated in the AI Research Building, in close proximity to the Max Planck Institutes for Intelligent Systems and Biological Cybernetics, and participate in the two International Max Planck Research Schools (IMPRS) 'Intelligent Systems' and 'Mechanisms of Mental Function and Dysfunction'.

The position is open to candidates who have a PhD or Master’s  in in a quantitative discipline (e.g. computer science, maths, statistics, physics, electrical engineering, computational neuroscience), a genuine interest in interdisciplinary work at the interface of machine learning and neuroscience, and strong programming skills (ideally Python/PyTorch). Prior experience in deep learning, and/or in analysing neurophysiological data with statistical methods is advantageous.

The University seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of Tübingen.

PhD applicants are also expected to apply to the IMPRS 'Intelligent Systems', https://imprs.is.mpg.de.

Please submit your application materials to mls-sekretariatspam prevention@inf.uni-tuebingen.de, with subject 'Application: Postdoc/PhD DeepHumanVision'. Please include a CV, a brief statement of research interests, contact details of two referees and a work sample - anything that is genuinely your own work, e.g. a thesis, computer code, a research manuscript, an essay, or a publication. For postdoc applicants, we expect relevant prior publications.