Stellenausschreibungen

Aktuell sind mehrere Doktoranden- und Postdoktorandenstellen zu besetzen.

2 Doktorandenstellen - Erkenntnistheorie und Ethik der erklärbaren KI (m/w/d; E13 TV-L, 75%)

Am  Exzellenzcluster "Maschinelles Lernen: Neue Perspektiven für die Wissenschaft" der Universität Tübingen, in Zusammenarbeit mit dem Internationalen Zentrum für Ethik in den Wissenschaften (IZEW), sind

2 Doktorandenstellen - zur Erkenntnistheorie und zur Ethik der erklärbaren KI (E13 TV-L, 75%)

zum Herbst 2020 zu besetzen. Beide Stellen sind auf 3 Jahre befristet und sind Teil des von der Baden-Württemberg-Stiftung geförderten Projekts "Künstliche Intelligenz, Vertrauenswürdigkeit und Erklärbarkeit".

Doktorandenstelle 1: Erkenntnistheorie der erklärbaren KI

Die/er DoktorandIn wird in enger Zusammenarbeit mit Dr. Eric Raidl am Thema "Erklärbarkeit und (wissenschaftlicher) Erklärung" arbeiten. Ziel dieses Projekts ist es, erkenntnistheoretische und wissenschaftliche Erklärungsnormen zu identifizieren, und zu untersuchen, inwiefern diese die erklärbare KI einschränken sollen.

Anforderungen:
- ein ausgezeichneter MA-Abschluss in Philosophie oder Logik
- nachweisliches Interesse an interdisziplinärer Forschung
- einen starken Hintergrund, entweder in der Wissenschafts- oder Erkenntnistheorie. Kenntnisse in Logik oder Wahrscheinlichkeitstheorie sind empfohlen.
- gute Englischkenntnisse
- ausgezeichnete organisatorische Fähigkeiten

Doktorandenstelle 2: Ethik der erklärbaren KI

Die/er DoktorandIn wird in enger Zusammenarbeit mit Dr. Thomas Grote an "Den Normen Erklärbarer KI" arbeiten. Ziel dieses Projekts ist es, normative Kriterien für algorithmische Erklärungen zu identifizieren, die algorithmische Entscheidungen rechtfertigen und/oder vertrauenswürdig machen.

Anforderungen:
- ein ausgezeichneter MA-Abschluss in Philosophie
- nachweisliches Interesse an interdisziplinärer Forschung
- einen starken Hintergrund entweder in Ethik (weit gefasst) oder in Erkenntnistheorie (mit einem Interesse daran, Werkzeuge der Erkenntnistheorie auf moralisch relevante Fragen anzuwenden)
- gute Englischkenntnisse
- ausgezeichnete organisatorische Fähigkeiten

Angebot:
Die beiden DoktorandInnen werden in den Exzellenzcluster "Maschinelles Lernen - Neue Perspektiven für die Wissenschaft" der Universität Tübingen eingebettet. Zusätzlich zum Gehalt erhalten die DoktorandInnen ein Reisebudget für die Teilnahme an Sommerschulen sowie nationalen und internationalen Konferenzen.

Bitte senden Sie die üblichen Unterlagen (Anschreiben, kurzes Dissertationsexposé (~2 Seiten), Lebenslauf, Zeugniskopien, Publikationsliste - als einzelnes PDF; maximal 5 MB) bis zum 16. Juni 2020 an die Geschäftsstellestelle des Exzellenzclusters (ml-in-science@uni-tuebingen.de). Bitte geben Sie an, auf welche der 2 Stellen Sie sich bewerben. Fragen können an eric.raidlspam prevention@uni-tuebingen.de für die Stelle 1 und an thomas.grotespam prevention@uni-tuebingen.de für die Stelle 2 gerichtet werden.

Die Universität strebt eine Erhöhung des Anteils von Frauen in Forschung und Lehre an und bittet deshalb entsprechend qualifizierte Wissenschaftlerinnen nachdrücklich um ihre Bewerbung. Qualifizierte internationale Wissenschaftlerinnen und Wissenschaftler sind ausdrücklich aufgefordert, sich zu bewerben. Schwerbehinderte werden bei gleicher Eignung bevorzugt berücksichtigt.

Post-doc in Interpretable Methods in Machine Learning (E13 TV-L, 100%)

The Chair for Explainable Machine Learning (Prof. Dr. Zeynep Akata) in the Cluster of Excellence „Machine Learning – New Perspectives for Science“ and in the Department of Computer Science at Eberhard Karls University Tübingen are currently looking for a

Post-doc in Interpretable Methods in Machine Learning (E13 TV-L, 100%)

starting as soon as possible. The initial contract will be for two years.

About the position
We are looking for a postdoc to join our new lab working on explainable machine learning in the intersection between machine learning, computer vision and natural language processing. The ideal candidate should hold a PhD in computer science, mathematics, cognitive science, neuroscience, statistics, 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 are required. This position will start as soon as possible.

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.

About the institute
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 research directions and try new ideas and structures. Our institute is multidisciplinary, has excellent facilities and outstanding infrastructure, is closely linked to the Max Planck Institutes and offers 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. Here you can find out more about Tübingen.

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. Here you can learn more about the University and the Cyber Valley initiative.

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: Postdoc 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. Applications will be reviewed starting from 15 May 2020 and until the position is filled. 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 and PhD positions - Machine Learning in Translational Single Cell Biology

The Clinical Bioinformatics group at the University Hospital/University of Tübingen invites applications for several

Postdoctoral position (TV-L E13, 100%) and PhD positions (TV-L E13, 65%) - Machine Learning in Translational Single Cell Biology

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

The available positions focus on projects developing and applying machine learning methodology to high dimensional, spatial proteomic/transcriptomic single-cell data in translational research in oncology, immunology and infectiology.

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/transcriptomic experiments are a plus, a solid background in mathematics, statistics, machine learning and programming is required to carry out the planned algorithm developments and data analysis.

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.

For further information about the position, please contact Manfred Claassen by e-mail, manfred.claassenspam prevention@med.uni-tuebingen.de, and visit our website. 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.

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.

PhD position (m/f/d, E13 TV-L, 65%) – Behavioral (sports) economics and Bayesian modelling

The Cluster of Excellence „Machine Learning – New Perspectives for Science“ at the University of Tübingen invites applications for a

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

to be filled as soon as possible.

The position is limited to three years. Depending upon the qualifying university degree of the applicant, affiliation with the International Max Planck Research School for Intelligent Systems (IMPRS-IS) is possible.

The call is aimed at young scientists with a very good university degree in computer science, mathematics, economics/econometrics, quantitative psychology/psychometrics, or sports science/sport informatics, advanced programming skills in R, and an interest in examining applications of machine learning methods in an interdisciplinary research project at the intersection of economics, psychology and sports science.

In this project, a theoretical focus is put on behavioral (sports) economics. A methodological focus is put on the development and application of Bayesian (dynamic latent variable) models that blend properties of multilevel models, time series models and generalized additive models. Content wise, the project is focused on behavioral responses to emotional cues in sports settings by exploiting intensive longitudinal multilevel data.

Principal Investigators are Tim Pawlowski and Augustin Kelava.

Applications with the usual documents (letter of application, curriculum vitae, copies of certificates, publication list) should be sent in electronic form (as a single PDF, at most 5 MB) to either tim.pawlowskispam prevention@uni-tuebingen.de or augustin.kelavaspam prevention@uni-tuebingen.de before 15th of May 2020. Questions can also be directed to either of them.

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

Job Offer [PDF]

PhD position (m/f/d, E13 TV-L, 65%) - Advancing Statistical Physics with Equation Learning

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

PhD position (TV-L E13, 65%)

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

We are looking for a young scientist with a very good university degree in physics or mathematics with an affinity to computer science and machine learning interested in an interdisciplinary research project.

In the project, equation learning networks shall be developed for applications in statistical physics (classical density functionals for fluids with directional interactions).
Principal investigators are Georg Martius and Martin Oettel.
The PhD position is fully funded (Salary level TV-L E13, 65%).

Applications with the usual documents (letter of motivation, curriculum vitae, copies of certificates, publication list) should be sent in electronic form (as a single PDF, at most 5 MB) to martin.oettelspam prevention@uni-tuebingen.de. Enquiries can be sent to martin.oettelspam prevention@uni-tuebingen.de and georg.martiusspam prevention@tuebingen.mpg.de.

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. Severely disabled persons with equal aptitude will be given preferential consideration.