Open positions

Currently there are several positions to be filled.

Postdoc Research Fellow (m/f/d; E13 TV-L, 100%) in Cumulative Culture in AI

The “Human and Machine Cognition” lab led by Dr. Charley M. Wu in collaboration with the “Tools and Culture among Early Hominins” lab and the ERC STONECULT project led Dr. Claudio Tennie invite applications for a

Postdoc Research Fellow (m/f/d; E13 TV-L, 100%, 2 years)

on the topic of Cumulative Culture in AI. Our aim is to better understand the human capacity for cumulative culture by developing AI that can distill and transmit social information in a human-like manner. Key ingredients of human social learning we want to model in AI systems include: representational exchange between social and individual learning systems, compositionality of individual knowledge with social information, and the inference of causal structure from partial/failed solutions. Just as the “cultural explosion” launched the success of the human species, a similar capacity for cultural learning has the potential to unlock more robust, interpretable, and compositional forms of AI. Note that the exact topic and subtopics are flexible and will depend on the interests of the candidate. For inquiries, please contact: charley.wuspam prevention@uni-tuebingen.de

About the position:

This interdisciplinary collaboration brings together a unique fusion of expertise, combining innovations in the computational modeling of human behavior and social learning (Dr. Charley Wu), with ground-breaking comparative research into the emergence of culture in humans, hominins and great apes (Dr. Claudio Tennie).

The ideal candidate should have a strong computational and mathematical background, for instance, in machine learning, reinforcement learning, multi-agent simulations, cognitive modeling, or a related area. This position is particularly suited for promising researchers recently finished or about to finish their PhD in a relevant discipline, such as cognitive science, computer science, psychology, computational neuroscience, statistics, or biology. A PhD must be completed before the start of the position.

Candidates should have worked in or have a strong passion for studying cultural evolution, social learning, and cognitive science, with a general interest and capacity for interdisciplinary research. Please indicate in your application if you have prior experience with conducting human experiments, computational modeling, and/or machine learning, which are beneficial but not required. Skills in programming languages (e.g., Python, R, Matlab, Javascript, Java, etc.), developing online or VR experiments, writing (in English), and the ability to independently manage a project (of any type) should also be mentioned.

What we offer:

The position is funded by the Tübingen AI Center, which is associated with University of Tübingen and is the highest ranked academic institution in artificial intelligence in the European Union. In addition, the position is also embedded in the Machine Learning excellence cluster and the Department of Early Prehistory and Quaternary Ecology. There are no formal teaching duties, allowing full flexibility for conducting research. There will be opportunities to mentor and work with PhD students working on related topics.

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 research statement describing your relevant interests (max 1 page), your CV, the names and email addresses of 2-3 referees, and unofficial copies of your University degrees as a single PDF to Charley Wu (charley.wuspam prevention@uni-tuebingen.de). If not included in your CV, please also include links to publicly available code examples (e.g., github, OSF, etc…). 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@ August 15th, 2022.

Research Fellow (m/f/d; E14 TV-L, 100%) in Explainable Machine Learning

The Explainable Machine Learning research group (lead by Prof. Dr. Zeynep Akata) in the Cluster of Excellence Machine Learning and the Department of Computer Science at the University Tübingen in collaboration with Prof. Dr. Trevor Darrell from the University of California, Berkeley are currently looking for an

Explainable Machine Learning Research Fellow (m/f/d; E14 TV-L, 100%)

starting as soon as possible. The position is especially suited for promising researchers after their PhD or post-doctoral research. The ideal candidate should hold a PhD in computer science,
mathematics, cognitive science, or any other related discipline. Experience with machine learning and vision-based deep learning and a record of publishing in top-tier peer-reviewed conferences (ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, EMNLP etc.) and/or journals (TPAMI, IJCV, JMLR, PNAS etc.) are required. The position is available for two years with a salary according to the German public sector (E14 TV-L).

As a new research fellow, you will have a high degree of independence and can work on a topic of your own choice within the general framework of Explainable Machine Learning, mentored jointly by Prof. Dr. Zeynep Akata from the University of Tübingen and Prof. Dr. Trevor Darrell from UC Berkeley. You will be integrated in the Explainable Machine Learning research group (currently 3 postdoctoral researchers and 9 PhD researchers) and will have the opportunity to collaborate with the members of the research group. In the second year, in the summer, you will have the opportunity for a research visit in the research group of Prof. Dr. Trevor Darrell at UC Berkeley.

About the group:

Our group conducts research on explainable multimodal machine learning. We study the challenging problem of large-scale representation learning using conditional generative models and weakly supervised learning that combine vision and language. We use image labels when they are available or side information in the form of attributes, descriptive sentences, keypoint locations, human gaze fixations or rough sketches when image labels are not provided. We combine several Computer Vision, Machine Learning and Natural Language Processing methods in a single framework that is generalizable across different tasks. Our aim is to improve the transparency of existing automatic decision makers and building interpretable AI systems while maintaining a high accuracy using minimal supervision. More information about our group: https://eml-unitue.de/

We are a part of the Cluster of Excellence Machine Learning at the University of Tübingen. Clusters of Excellence are, arguably, the most influential line of funding by the German Research Foundation (DFG). With its goal to sharpen the research profile of German universities the idea is to support internationally competitive disciplines at selected sites. In the current funding round, 57 such clusters were established or received an extension, each with a funding of up to 50 million Euros for 7 years, starting in 2019. With the funding provided by the Excellence Strategy and the existing research environment in Tübingen, our cluster has the best starting conditions to pursue interesting researchdirections and try new ideas and structures. Our group is closely linked to the Max Planck Institutes of Intelligent Systems and for Biological Cybernetics in Tübingen and Max Planck Institute for Informatics in Saarbrücken. Through the ELLIS PhD/Postdoc program we have actively ongoing collaborations with Google Deepmind, Google Research in Paris and INRIA Grenoble. We offer a superb international research environment operating in the English language.

About Tübingen:

Tübingen is a scenic medieval university town. The quality of life is exceptionally high and the atmosphere is both tolerant and inclusive. The old town is a sight in itself, with marvellous old buildings dating back to the 15th century, an old botanical garden, many churches and cobblestone alleys. Numerous sidewalk cafes, wine taverns, pubs, restaurants and parks add to the atmosphere. You can find out more about Tübingen here: tuebingenresearchcampus.com

Tübingen offers excellent research opportunities due to four Max Planck institutions, the University as well as the Tübingen AI Center. Similarly, the Cyber Valley initiative hosts several industrial research centers such as the Bosch Center for AI, Amazon Research etc. focusing on machine learning research. The University of Tübingen hosts around 4900 researchers and 27200 students studying in 200 programs. You can learn more about the University and the Cyber Valley initiative from: https://uni-tuebingen.de/en and https://cyber-valley.de/en

How to apply:

Please email a cover letter, CV and research proposal (up to 4 pages including references), as well as the names and email addresses of 2 referees to zeynep.akataspam prevention@uni-tuebingen.de, please use the following subject line in your email: Research Fellow Application - Interpretable Methods in ML. If you have any questions about the position, the research group, or anything else, please do not hesitate to contact us directly. The application deadline is 15th February 2022. 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 position (m/f/d; E13 TV-L, 75%) on Algorithmic Fairness in Healthcare

The Cluster of Excellence "Machine Learning - New Perspectives for Science" at the University of Tübingen advertises a

PhD position (m/f/d; E13 TV-L, 75%) on Algorithmic Fairness in Healthcare

to be filled in May 2022. The position is limited to four years. The position is part of the project „Certification and Foundations of Safe Machine Learning Systems in Healthcare“, funded by the Carl Zeiss Stiftung.

The doctoral student will do independent research on issues of fairness in healthcare from a philosophical/normative perspective, while potentially also doing interdisciplinary work in collaboration with ML researchers. The doctoral student will be supervised by Dr. Thomas Grote. Tübingen has a very active scene in the philosophy of AI/ML and has emerged as a hotspot for research in ML.

Requirements:

  • an excellent MA degree in philosophy
  • a strong background in either ethics (broadly construed), philosophy of AI/ML, or philosophy of science
  • good writing skills
  • demonstrable interest in interdisciplinary research
  • proficiency in English
  • excellent organizational skills

Offer:

The PhD student will be embedded in the Cluster of Excellence “Machine Learning – New Perspectives for Science” at the University of Tübingen. The salary is above the German standard for PhD positions (according to the DFG) and comes with a travel budget. Please send the usual documents (cover letter, short research proposal, curriculum vitae, writing sample, copies of certificates, list of publications and letters, if available, as a single PDF; not exceeding 5 MB) by the deadline of February 15, 2022 to thomas.grotespam 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. Applications from other groups underrepresented in philosophy are also strongly encouraged. 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 researcher position (m/f/d, E13 TV-L, 100%) Mathematical and Computational Population Genetics

The newly founded independent junior research group „Mathematical and Computational Population Genetics“, headed by Franz Baumdicker at the University of Tübingen has an opening for

Postdoctoral researchers (m/f/d, E13 TV-L, 100%)

The group develops and applies mathematical models and bioinformatic tools with a special focus on microbial evolution. We are interested in a variety of evolutionary scenarios including CRISPR Cas Evolution, Pan-Genome Evolution, Horizontal Gene Transfer, Fluctuationg Selection, and Cooperation in Bacteria.

The postdoc should be interested to operate at the intersection of Mathematical Population Genetics / Computational Biology / Bioinformatics using mathematical population genetics, phylogenetics, statistical analysis, machine learning algorithms, and large scale simulations to derive new mathematical results, develop open source software and apply them to (microbial) genome data.

For scientific questions please contact: franz.baumdicker@uni-tuebingen.de.

Candidate profiles we would love to see:

  •  PhD degree in (Bio-)Mathematics, Statistics, Bioinformatics, Computational Biology or a related field
  • Interest in interdisciplinary research
  • Strong mathematical preparation and interest and/or good computational skills (e.g. in Python, R)
  • Independent, responsible and committed work
  • Fluency in (scientific) English

What we offer:

  • Salary according to TV-L, E13 (100%)
  • The group is part of two Excellence Clusters (Controlling Microbes to Fight Infections & Machine Learning) in Tübingen, which offers an excellent research environment with plenty of potential collaboration partners.
  • Flexible starting date and the possibility to start the project remotely in the initial phase
  • Focus on research (no formal teaching duties)
  • Intense personal and scientific mentoring in an open and supportive environment
  • Integration into a young and agile research group
  • Responsibility to conduct your own research projects with a high amount of autonomy
  • The opportunity to visit and organize conferences, workshops and research visits to other universities and summer schools.
  • Possibilities to develop your own research ideas and mentor Ph.D. students

The University of Tübingen is an Equal Opportunity Employer with a strong institutional commitment to excellence through diversity. All qualified applicants will be considered for employment without regard to gender, race, color, national origin, sexual orientation, religion, disability, or age. Researchers from outside Germany are particularly encouraged to apply.

Applications and inquiries should be sent to franz.baumdickerspam prevention@uni-tuebingen.de.

Please send your application as a single PDF file and include a brief statement on your interests and experience, CV (including a possible list of publications and the contact info of two academic references), and university transcripts.

The applications are reviewed on a rolling basis and continue until the position has been filled.

PhD position (m/f/d, E13 TV-L, 65%) Mathematical and Computational Population Genetics

The newly founded independent junior research group „Mathematical and Computational Population Genetics“ headed by Franz Baumdicker at the University of Tübingen has an opening for

PhD students )m/f/d, E13 TV-L, 65%)

The group develops and applies mathematical models and bioinformatic tools with a special focus on microbial evolution.

The PhD students will work at the intersection of Mathematical Population Genetics / Computational Biology / Bioinformatics using population genetics, phylogenetics, statistical analysis, machine learning algorithms, and large scale simulations to derive new theoretical results, develop open source software and apply them to (microbial) genome data.

We are interested in a variety of evolutionary scenarios including CRISPR-Cas Evolution and Dynamics, Pan-Genome Evolution, Horizontal Gene Transfer, Fluctuationg Selection, and Cooperation in Bacteria.

For scientific questions please contact: franz.baumdicker@uni-tuebingen.de.

Candidate profiles we would love to see:

  • Master's degree in (Bio-)Mathematics, Statistics, Bioinformatics, Computational Biology or a related field
  • Interest in interdisciplinary research
  • Strong mathematical preparation and interest and/or good computational skills (e.g. in Python, R)
  • Independent, responsible and committed work
  • Fluency in (scientific) English

What we offer:

  • Salary according to TV-L, E13 (65%)
  • Dissertation at the Faculty of Natural Sciences working with two advisors
  • The group is part of two Excellence Clusters (Controlling Microbes to Fight Infections & Machine Learning) in Tübingen, which offers an excellent research environment with plenty of potential collaboration partners.
  • Possibly integration into the DFG priority programme SPP2141, where appropriate
  • Focus on research (no formal teaching duties)
  • Intense personal and scientific mentoring in an open and supportive environment
  • Integration into a young and agile research group
  • The opportunity to visit conferences, workshops, other research groups and summer schools
  • Responsibility to conduct your own research projects with a high amount of autonomy
  • Possibilities to develop your own research ideas in a young and agile team

The University of Tübingen is an Equal Opportunity Employer with a strong institutional commitment to excellence through diversity. All qualified applicants will be considered for employment without regard to gender, race, color, national origin, sexual orientation, religion, disability, or age. Researchers from outside Germany are particularly encouraged to apply.

Applications and inquiries should be sent to franz.baumdickerspam prevention@uni-tuebingen.de.

Please send your application as a single PDF file and include- brief statement on the applicant's interests and experience, CV (including a possible list of publications and the contact info of two academic references), and university transcripts.

The applications are reviewed on a rolling basis and continue until the positions have been filled.

Doctoral Research Assistant (m/f/d, E13 TV-L, 65%) Clinical Bioinformatics

A position is open for a postdoctoral research assistant in the Clinical Bioinformatics group at the University Hospital/University of Tübingen. The available position focuses on development and application of machine learning approaches for the simulation based reconstruction of differentiation processes of immune cells during viral infections.

We are looking for you as of now, or upon agreement, as a

Doctoral Research Assistant (m/f/d, E13 TV-L, 65%)

The position will involve research in the interdisciplinary consortium comprising researchers at Universities of Tübingen and ETH Zurich. Research in this consortium builds on its recent work on T cell exhaustion in chronic infection (Sandu et al. 2020, Cerletti et al. 2020, Gupta et al. 2020).

This position is part of an initiative investigating T cell exhaustion, an immune cell state associated with persistent viral infections as well as with impaired host immune defense in cancer affecting more than 2 billion people worldwide. The causal molecular mechanisms leading to exhaustion remain elusive due to the difficulty to account for the complex and dynamic interplay of regulators of T cell differentiation in vivo. We aim at identifying novel causal transcriptional mechanisms with an integrated multiplexed, in vivo, single-cell intervention screen and causal inference approach. We will perform a multiplexed single-cell CROP-seq intervention screen in conjunction with time series single cell RNA seq readout of antigen specific CD8+ T cells in the course of chronic infection. We propose deriving causal Markov models from the resulting data by comparative and integrative RNA velocity analysis building on our recent simulation based trajectory inference approach (Gupta et al. 2020). The method development and application to this end constitutes the core goal for the advertised position.

This approach will generate testable hypotheses on specific driver genes deciding on the fate of CD8+ T cells. In conjunction with our international partners we will validation the fate determining potential of these genes will be performed in vivo by selective targeting in LCMV-specific CD8+ T cells. Validated mechanisms and driver genes in our in vivo model system will motivate rational interventions to beneficially interfere with T cell exhaustion in the context of human chronic infections or cancer.T

The ideal candidate brings along a degree that demonstrates an interdisciplinary background in both life and formal sciences. While a background cancer-/immune biology  and single cell proteomic experiments are a plus, a solid background in mathematics, statistics and programming is required to carry out the planned algorithm developments and data analysis. A fluent level of English is mandatory. We are looking for a highly motivated candidate with excellent communication skills that is capable of working in an interdisciplinary environment and can team up with scientists for experimental as well as computational analysis. The candidate should have a high degree of initiative. We offer work in a highly stimulating environment with state-of-the-art infrastructure, providing the successful applicant with unique opportunities to develop a strong interdisciplinary portfolio in both experimental and computational biology.

The University aims to increase the proportion of women in research and teaching and therefore urges suitably qualified women scientists to apply. Qualified international researchers are expressly invited to apply. Disabled persons with equal aptitude will be given preferential consideration.

Applications with a motivation letter, full CV, diploma(s) and two contacts for further references should be sent online to manfred.claassenspam prevention@med.uni-tuebingen.de.