Open positions

Currently there are several positions to be filled.

Researcher in scientific ML (m/f/d) TV-L E13, 100%

Are you passionate about probabilistic machine learning (ML), scientific datasets and clean performant code? Would you like to feed your passion for science on cutting-edge research, from archaeology to quantum physics? Do you look forward to solving inference problems with the outstanding minds in the Tübingen ML community?

The mlcolab (Machine Learning ⇌ Science Colaboratory) is looking for you! We are reaching out to enhance our team with a motivated, skilled researcher working at the intersection of science, engineering, and people.
The position is for three years.

About us
We want to raise the power of scientific discovery by thoughtful application of machine learning techniques — closely working together with the ML researchers and the research community of the University, spanning the natural sciences, the social sciences and the humanities. We explain our mission in depth at https://mlcolab.org/mission.

We are building a team to tackle this challenge from different angles

  • We develop, implement and deploy probabilistic models for varied research problems, from reconstructing bone surfaces from point-cloud data, to finding parameters for complex and realistic physical simulations, to classifying microscopic pollen grains, to analysing ancient texts. Have a look at https://mlcolab.org/projects
  • We train and advise researchers on the best methods to obtain maximum insight from their data, from feature selection to model evaluation.
  • We assess best practices in scientific machine learning, and share our progress with the community in conventional as well as interactive formats.
  • Finally, we distill recent literature into open-source machine learning code to facilitate realistic and unbiased algorithm benchmarking and to empower researchers across disciplines.

Your role
You will be contributing your experience towards developing models and software, coaching and giving advice, preparing publications, designing compelling explanations and delivering them to postgraduate audiences. You will interact with scientists and ML researchers to set up joint projects, sometimes leading teams to carry them out. Our group is collegial and collaborative with access to exciting datasets and ML expertise in our research network that facilitate formulating projects aligned with our mission and your interests.

Your profile
You possess an excellent M.Sc. or PhD degree in a quantitative discipline (mathematics, physics, computer science, etc), good programming skills and hands-on experience training ML models.
All other qualifications below are just preferred: none of us walked in with all of them. If a few of these points apply to you, we want to talk to you!

  • A command of probabilistic modelling enabling you to read and explain recent machine learning research.
  • Applied software skills such as designing documented, composable API, vectorising/parallelising sequential code, leveraging developer tooling (CI, git, docker...).
  • Fluency with the Python and/or Julia data science and differentiable computing stacks (scikit-learn, pandas, pytorch, jax, pyro, mlj, flux, turing...).
  • Willingness to communicate complex ML methods to domain scientists and domain problems to ML researchers, and a drive to improve on current explanation formats by using interactive media.
  • Coaching and lateral leadership skills to interact with our own and other PhD and MSc students, as well as collaborators.

We are looking for a balanced team and will help each other grow where required.

Tübingen for research and life
Tübingen is a scenic university town on the Neckar river in South-Western Germany with an  exceptionally high quality of life and a welcoming, diverse and inclusive atmosphere. In Tübingen, you will find a young international environment where most locals speak English. Thanks to the University, four Max Planck institutes, the University Hospital, and Europe’s largest AI research consortium, Tübingen offers an intellectually stimulating atmosphere.
This network is a stone's throw away from your office at the brand-new Tübingen AI Research Center, where you can enjoy beautiful views, great coffee, lots of social interactions with friendly colleagues, and excellent hardware at your desk and in our powerful ML Cloud.

What is important to us
We care about caring — and look for people who deeply care about every member in the team and our joint endeavor, with an eye for detail and an appreciation of excellence.
We are open-minded about how you organize your working schedule in order to accommodate different rhythms of life, including caring for the kids or the elderly.
We strive to keep constantly learning and put time aside for that. To learn best not only from books but also from human interactions, we encourage kind, honest, and constructive feedback. We distribute work based on motivation and competence, not titles. And we stand behind our work as a team.
We believe that diversity in age, abilities, sexuality, gender identity, ethnicity, perspectives and ideas makes not just for a richer life, but also for a better team outcome. And we know that people do their best work when they feel like they belong — included, valued, and equal. This is the environment we want to build, where everyone brings their full selves to work knowing that they’ll be supported to succeed. We hope you’ll join us.

How to apply
For questions about the job, write to Álvaro (alvaro.tejero—uni-tuebingen.de). To apply, send a single pdf file <lastname>.pdf to Elena (elena.sizana—uni-tuebingen.de) including:

  • a letter explaining why you'd like to be part of the team and how you can contribute,
  • a transcript of records of your master degree (and PhD degree if applicable),
  • your curriculum vitae and contact details of two or three people who have worked with you, and
  • links to code you have written, talks you have given and papers you have published, if applicable. Where unavailable online you can add a separate file.

Applications received until 31.12.2020 will receive full consideration.

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.

E 13 TV-L
According to the general pay scale of German universities, the salary will be “E 13 TV-L”. Depending on your experience, the University administration will place you in a certain level. You can find a salary calculator, with gross and net at https://cutt.ly/uheEtC0.

Job Ad Print version [PDF]

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.

Application deadline: November 02, 2020.

2 PhD positions - Human and Machine Cognition Lab (m/w/d; E13 TV-L, 65%)

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

Two PhD positions (m/f/d; E13TV-L, 65%)

to be filled as soon as possible. Both positions are limited to three years.

About the group
The HMC lab is led by Dr. Charley M. Wu and seeks to understand the computational strategies that allow humans to perform massively scalable inference and rapidly adapt to novel environments, both alone and in social environments. This research aims to use insights from human cognition to improve machine learning methods, while also using advances in machine learning as tools for understanding human intelligence.

Current research topics include generalization and efficient exploration in large problem spaces, the learning of map-like representations in spatial and non-spatial environments, social search dynamics in virtual environments, and cumulative cultural evolution in online communities. 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 also 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 havea 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 and inclusive. Most locals speak English and knowledge of German is not required to live here. 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 the Central Office of the Cluster of Excellence (ml-in-sciencespam prevention@uni-tuebingen.de). If you have any questions about the position, please do not hestitate to directly contact Charley Wu (charleymswu@gmail[dot]com).
The university seeks to raise the number of women in research and teaching and therefore urgesqualified 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. Applications received by December 14th , 2020 will receive full consideration.

1-2 PhD Positions (m/f/d; E 13 TV-L, 65%) - Ethics and Epistemology

Dr. Konstantin Genin, leader of the "Ethics and Epistemology" research group in the Cluster of Excellence: "Machine Learning - New Perspectives for Science" at the University of Tübingen, advertises

1-2 PhD Positions (m/f/d E 13 TV-L, 65% - 36 Months)

to be filled ideally in early 2021. Both positions are funded for 3 years.

It is widely acknowledged that questions of scientific methodology depend on ethical ones. If an experiment is unethical, it ought not to be performed. If an algorithm is unfair, it ought not to be implemented. From this perspective, ethics responds to methodological advances by rushing to install new guard-rails. But ethical questions also depend on methodological ones. Whether an experiment is ethical depends on whether similarly reliable inferences could be made from non-experimental data. Whether an algorithm is fair depends on how well it manages delicate tradeoffs between competing explications of fairness. The answers to these questions typically turn on methodological ones and -- more often than not -- these are both technical and hotly contested. From this perspective, methodological advances ought to lead to ethical ones. The goal of the "Ethics and Epistemology" research group is to work these problems from both sides: to approach methodological issues with an eye to their social consequences and to approach ethical issues with an eye to methodological resolutions.

Relevant topics include but are not limited to:

- causal discovery from observational and experimental data
- algorithmic fairness
- statistics and the social sciences
- learning theory
- values in science

Applicants must already hold an MA degree in philosophy, statistics, machine learning or an allied social science field. Applicants should be proficient in English and interested in formal approaches to philosophical issues. Applicants already holding a PhD should refer to the parallel call for postdoctoral researchers.

Compensation is at minimum €2601/month brutto (€1688 netto) and increases according with experience. Funding for equipment, travel and other expenses is also available. Students interested in the intersection of ethical and methodological questions in statistics, machine learning, artificial intelligence and the medical and social sciences are encouraged to apply.

Please send the usual documents (cover letter, short (1 page) research proposal and academic CV) as a single PDF to the Central Office of the Cluster of Excellence (ml-in-sciencespam prevention@uni-tuebingen.de) by the deadline of December 18th 2020. The group aims to decide on candidates by mid-January. Questions can be directed to konstantin.geninspam prevention@uni-tuebingen.de.

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.

Postdoctoral position (m/f/d; E13 TV-L, 100%) - Ethics and Epistemology

Dr. Konstantin Genin, leader of the "Ethics and Epistemology" research group in the Cluster of Excellence "Machine Learning - New Perspectives for Science" at the University of Tübingen, advertises

1 Postdoc Position (m/w/d; TVL E13, 100% - 36 Months)

to be filled ideally in early 2021.

It is widely acknowledged that questions of scientific methodology depend on ethical ones. If an experiment is unethical, it ought not to be performed. If an algorithm is unfair, it ought not to be implemented. From this perspective, ethics responds to methodological advances by rushing to install new guard-rails. But ethical questions also depend on methodological ones. Whether an experiment is ethical depends on whether similarly reliable inferences could be made from non-experimental data. Whether an algorithm is fair depends on how well it manages delicate tradeoffs between competing explications of fairness. The answers to these questions typically turn on methodological ones and -- more often than not -- these are both technical and hotly contested. From this perspective, methodological advances ought to lead to ethical ones. The goal of the "Ethics and Epistemology" research group is to work these problems from both sides: to approach methodological issues with an eye to their social consequences and to approach ethical issues with an eye to methodological resolutions.

Relevant topics include but are not limited to:

- causal discovery from observational and experimental data
- algorithmic fairness
- statistics and the social sciences
- learning theory
- values in science

Applicants must already hold an PhD degree in philosophy, statistics, machine learning or an allied social science field. Applicants should be proficient in English and interested in formal approaches to philosophical issues. Candidates without a doctoral degree should see our parallel call for PhD students.

The position is funded for 3 years. Compensation is at minimum €4002/month brutto (€2379 netto) and increases according with experience. Funding for equipment, travel and other expenses is also available. Students interested in the intersection of ethical and methodological questions in statistics, machine learning, artificial intelligence and the medical and social sciences are encouraged to apply.

Please send the usual documents (cover letter, short (1 page) research proposal, academic CV) as a single PDF to the Central Office of the Cluster of Excellence (ml-in-sciencespam prevention@uni-tuebingen.de) by the deadline of December 18th 2020. Recommendation letters, if available, can be mailed separately to the same address. The group aims to decide on candidates by mid-January. Questions can be directed to konstantin.geninspam prevention@uni-tuebingen.de.

The University aims to increase the proportion of women in research and teaching and therefore urges suitably qualified women scientists to apply. The "Ethics and Epistemology" group also welcomes applications from other groups underrepresented in philosophy and machine learning. Qualified international researchers are expressly invited to apply. Disabled persons with equal aptitude will be given preferential consideration.

PhD and Postdoc positions @ Dept Sensory + Sensorimotor Systems, MPI Biological Cybernetics

Several job openings at the Department for Sensory and Sensorimotor Systems, Max Planck Institute for Biological Cybernetics, headed by Cluster member Prof. Li Zhaoping

Our research in neuroscience aims to discover and understand how the brain receives and encodes the sensory input (vision, audition, tactile sensation, and olfaction) and processes the information to direct body movements as well as to make cognitive decisions. The research is highly interdisciplinary, and uses theoretical as well as experimental approaches, including human psychophysics and animal behavior, fMRI, electrophysiology and computational modelling to answer questions for example about visual illusions, attention, object recognition and saliency.


Find all job openings here

Tenure-Track Professor of Software Engineering (m/f/d)

The Department of Computer Science of the Faculty of Science at the University of Tübingen, Germany, invites applications for the position of

Tenure-Track Professor of Software Engineering (m/f/d)

Starting date: January 1, 2021.

A successful candidate for this position will strengthen the education of students in all computer science and cognitive science programs. The position has a teaching load of four hours per week prior to interim evaluation, and six hours thereafter.

The Department of Computer Science seeks applications from outstanding individuals who have a proven international record of excellent research in the area of software engineering, in particular in one or more of the following research topics:

  • Software Development (Continuous Integration, DevOps, Refactoring, Recommender Systems,
  • Projectional Editing, Reverse Engineering, Software Life Cycle, Product Line Engineering)
  • Program Comprehension and Visualization (Program Analysis)
  • Software Validation (Testing, Debugging)
  • Non-sequential Programs (asynchronous, concurrent, probabilistic)
  • Repository Mining (Data Mining for Software Engineering)
  • Didactics of Programming and Software Engineering
  • Software Security

The chosen candidate will contribute to the central area of practical computer science. Participation in academic self-administration of the university and in the committees of the Department of Computer Science are expected. The successful candidate has the opportunity to contribute to the Cyber Valley Initiative of the state of Baden-Württemberg and the new Cluster of Excellence "Machine Learning in Science".

Required qualifications include an outstanding doctoral thesis in a pertinent field, recognizable potential for internationally visible publications in leading international peer-reviewed journals, successful grant applications, and teaching experience.

Applicants for a tenure-track professorship with a PhD from Tübingen must have changed universities after completing their doctorates or have worked in academia for at least two years somewhere other than the University of Tübingen.

If the final evaluation after six years is positive, this professorship will be upgraded to a full (W3) professorship with no re-advertising of the position. Detailed information on the criteria underlying the interim evaluation and promotion to the tenured position may be found in our guidelines for tenure review under the following link: https://uni-tuebingen.de/en/faculties/faculty-of-science/faculty/service-downloads/#c608746. There you can also find information on this employment category.

The University of Tübingen is particularly interested in increasing the number of women in research and teaching and therefore strongly encourages women candidates to apply. In line with its internationalization agenda, the university welcomes applications from researchers outside Germany. Applications from equally qualified candidates with disabilities will be given preference.

Applicants must be in an early stage of their career; those who have completed a habilitation will therefore be excluded.

Applications with supporting documents (cover letter, Curriculum Vitae, list of publications and teaching experience, certificates/diplomas) as well as a teaching statement and a research statement including collaboration plans, along with the completed application form (https://uni-tuebingen.de/en/faculties/faculty-of-science/faculty/service-downloads/#c608746) should be sent by email as a single PDF-file to the Dean of the Faculty of Science, University of Tuebingen, Germany (careerspam prevention@mnf.uni-tuebingen.de) by November 27, 2020. Enquiries may be directed to this address.