Stellenausschreibungen

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Studentische Hilfskraft (35h im Monat), Machine Learning in Medical Image Analysis Group

The Machine Learning in Medical Image Analysis Group invites applications for a

Student Research Assistant Position (35h per month)

Project

A major limitation of deep learning for medical applications is the scarcity of labelled data. Meta-learning, which leverages principles learned from previous tasks for new tasks, has the potential to mitigate this data scarcity. However, most meta-learning methods assume idealised settings with homogeneous task definitions. The most widely used family of meta-learning methods, those based on Model-Agnostic Meta-Learning (MAML), require a constant network architecture and therefore a fixed number of classes per classification task.

We take a first step in the direction of making meta-learning algorithms, suitable for more realistic medical problems by investigating different strategies for training and testing with a variable
number of possible labels.

To this end, we are currently assembling a dataset and writing a PyTorch toolbox for testing meta-learning algorithms in a real-
istic medical setting. We aim to make our dataset and toolbox publicly available and to issue a challenge for the MICCAI 2023
conference. For more information visit our project website and watch the linked video.

Your tasks

You will aid in assembling the dataset for the challenge and writing the PyTorch medical meta-learning toolbox. Your main tasks will include collecting meta-information in a structured way for multiple source datasets and writing PyTorch dataset classes facilitating meta-learning on these datasets.

Your profile

  • Good knowledge of Machine Learning and of Image Analysis/Computer Vision,
  • Interest in working with medical imaging datasets,
  • Interest in learning about and working on meta-learning,
  • Proficiency in Python, PyTorch and Git.

What we offer

  • HiWi salary according to the standard rates of the University of Tübingen,
  • A desk space in the Tübingen AI Research Building,
  • Insights into an exciting and trending research field,
  • The possibility of contributing to a scientific publication.

How to apply

If interested, please contact Stefano Woerner (stefano.woernerspam prevention@uni-tuebingen.de) and attach your CV and transcript of records to apply.

Fremdsprachensekretär/in (m/w/d, E9a TV-L 50%), Machine Learning ⇌ Science Colaboratory

Das Machine Learning ⇌ Science Colaboratory (ML Colab) ist eine zentrale Einrichtung des Exzellenzclusters “Machine Learning — New Perspectives for Science”. Wir suchen zum nächstmöglichen Zeitpunkt eine

Fremdsprachensekretär/in (m/w/d, E9a TV-L 50%)


Die Stelle ist zunächst befristet bis zum 31.12.2025.

Es besteht die Möglichkeit, die Position mit einer anderen derzeit ausgeschriebenen Stelle zu einer Anstellung in Vollzeit (100%) zu kombinieren, beispielsweise „Fremdsprachensekretär/in in der Geschäftsstelle des Exzellenzclusters „Maschinelles Lernen“.

Eine einschlägige Ausbildung im Bereich Fremdsprachensekretariat oder eine vergleichbare Qualifikation wird vorausgesetzt. Englisch ist als Fremdsprache obligatorisch, als zweite Fremdsprache sollte Französisch, Italienisch oder Spanisch beherrscht werden.

Ihre Hauptaufgaben sind  
•    Zusammenarbeit mit der Universität, z. B. bei der Einstellung von Personal, der Bestellung von Materialien und Planung unserer
     wissenschaftlichen Reisen
•    Organisation von Schulungen, Hackathons usw., einschließlich Korrespondenz und technischer Vorbereitungen
•    Verwaltung und Ausbau unserer Wissensdatenbank und internen Kommunikationsplattformen

Darüber hinaus erwarten wir Unterstützung bei der
•    Verfolgung von Meilensteinen und Berichterstattung über unseren Projektfortschritt
•    Kommunikation und Öffentlichkeitsarbeit über Newsletter, unsere Webseite, Twitter, Diskussionsforen...

Wir suchen eine proaktive Persönlichkeit, welche die Aufgaben gerne selbst in die Hand nimmt und vorantreibt, während sie sich bei Bedarf mit allen Beteiligten abstimmt. Erfahrungen mit Verwaltungs- und Managementaufgaben im Hochschul-/Forschungsbereich sind von Vorteil. Alle unsere internen Arbeitsabläufe sind digital, daher erwarten wir von Ihnen, dass Sie Online-Office-Anwendungen beherrschen und no-code Kollaborationstools und relationale Datenbanken kennen oder gerne erlernen möchten.

Wir bieten flexible Arbeitszeiten und ein anregendes Arbeitsumfeld in einem jungen, motivierten Team und einer partizipativen Kultur in einem internationalen Umfeld. Darüber hinaus haben Sie umfangreiche Entwicklungsmöglichkeiten in den Bereichen Projektmanagement, digitale Arbeitsabläufe und Anwendungen der Künstlichen Intelligenz (KI), sowohl berufsbegleitend als auch im Rahmen von Fachkursen. Als Universitätsmitglied haben Sie unter anderem auch Zugang zu einem umfassenden Sportprogramm.

Bitte senden Sie Ihre Bewerbung mit Lebenslauf, Motivationsschreiben und Zeugnissen in einer einzigen PDF-Datei bis zum 27. November 2022 an Álvaro Tejero Cantero alvaro.tejerospam prevention@uni-tuebingen.de. Die Universität Tübingen setzt sich für Chancengleichheit und Vielfalt ein. Schwerbehinderte werden bei gleicher Eignung bevorzugt berücksichtigt. Die Einstellung erfolgt über die Zentrale Verwaltung der Universität Tübingen.  

 

Postdoc Research Fellow (m/w/d; E13 TV-L, 100%) Representation Learning

The “Human and Machine Cognition” lab led by Charley M. Wu in collaboration with Peter Dayan of the Max Planck Institute for Biological Cybernetics and the University of Tübingen invite applications for a

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

on the topic of Representation Learning:  How do people represent an infinitely complex world despite finite cognitive resources? How do these representations balance learning efficiency, compositionality, ease of control, and multi-task generalizability?

Potential topics include:
●    Selective attention and generalization in naturalistic environments
●    Representational complexity and the explore-exploit tradeoff
●    The learning of useful primitives and abstractions for compositional reasoning
in addition to the interests of the candidate.

For inquiries, please contact: charley.wu[at]uni-tuebingen[dot]de

About the position:
This position is suited for researchers who have recently finished or are about to finish their PhD in a relevant discipline, such as computational neuroscience, cognitive science, computer science, or psychology. The ideal candidate is self-motivated, comfortable with both analytic and critical thinking, and has a strong computational and mathematical background. Relevant areas of expertise include reinforcement learning, machine learning, and cognitive modeling. Please indicate in your application if you have prior experience with conducting experiments, computational modeling, machine learning, and/or neuroimaging (EEG/fMRI/MEG). Links to publicly available code examples (e.g., github, OSF, etc…) should be provided to demonstrate programming proficiency.

What we offer:
The position is jointly funded by the Cluster of Excellence “Machine Learning: New Perspectives for Science” and an Alexander-von-Humboldt-Professorship award. The position is based at the University of Tübingen, but collaboration with the MPI Biological Cybernetics is expected. 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 plan (max 1 page), your CV, and contact information of two referees as a single PDF to Susan Fischer (susan.fischer[at]tue[dot]mpg[dot]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 arranged by the central administration of the University of Tübingen. Please submit your application by November 1st, 2022.

 

Mehrere Doktorandenstellen in Machine Learning Based Data Anaysis of Scattering and Diffraction Data

The Schreiber Group at the University of Tübingen works on the physics of molecular and biological materials using X-ray and neutron scattering. A specialised sub-group is dedicated machine learning based data analysis of scattering and diffraction data. Currently we have several

PhD positions (m/f/d)

available. Candidates with experience or interest in neural networks and machine learning strategies to analyse scattering are especially encouraged to apply.

You should have good communication skills, attention to detail, and flexibility to work both independently as well as in a team. You should hold either a diploma/master degree in physics, physical chemistry, material science or have a background in computer science.

You will be part of challenging interdisciplinary projects that are integrated into major national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium. We offer well-equipped laboratories, a highly collaborative international environment and affiliation with the Cluster of Excellence "Machine Learning: New Perspectives for Science" funded by the DFG and hosted at the University Tübingen. You will receive excellent training and for all our projects we offer the opportunity to perform research at international large-scale facilities (such as synchrotrons and neutron sources).  Details on our research as well as publications and background information can be found at http://www.soft-matter.uni-tuebingen.de/machine_learning_XRR.html and http://www.soft-matter.uni-tuebingen.de/machine_learning_GIWAXS.html

The University of Tübingen has ~ 28,000 students and more than 500 years of academic tradition. It has national excellence status as is ranked in the top 100 universities worldwide. You will benefit from a variety of training opportunities and language courses as well as the university’s graduate academy. See also https://uni-tuebingen.de/en/excellence-strategy.

Applications should include a cover letter describing research interests, achievements, motivation and capabilities; curriculum vitae; academic certificates; names and email addresses of two professional references (e.g., current or previous research advisors). The opening will remain valid until the position is filled.

The positions are available immediately. Salary will be determined according to the German collective wage agreement in public service. Please send your application within one PDF file to softmatterspam prevention@ifap.uni-tuebingen.de

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.

Doktorandenstelle (m/f/d; E13 TV-L, 65%, 3 years) in Data Science and Sport Economics

The Institute of Sports Science at the University of Tübingen invites applications for a

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

starting in autumn 2022 (limited to 3 years) with the objective of a scientific qualification (earning a PhD).

The position is assigned to the Department of Sport Economics, Sport Management & Media Research (Chair: Tim Pawlowski) and will be affiliated with the Data Science and Sports Lab.

The call is aimed at highly-motivated young scientists with a very good university degree in business / management, computer science, data science, economics / econometrics, mathematics, sports science / sport management / sport economics, or related subjects as well as an interest in exploring sports related data with quantitative research methods.

Tasks

  • Research in sport economics
  • Teaching in the Bachelor study program

Desirable competencies and experiences

  • High proficiency in both spoken and written English
  • Data literacy
  • Experience in quantitative research methods (econometrics / data science)
  • Experience in programming / statistical software packages (Python, R and/or STATA)

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 christina.toellespam prevention@uni-tuebingen.de before 5th of September 2022 (job interviews with potential candidates will take place mid / end of September).

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.

Doktorandenstelle (m/f/d; E13 TV-L, 65%, 3 years) in Neuro-Cognitive Modeling

The “Human and Machine Cognition” lab led by Dr. Charley M. Wu in collaboration with the “Neuro-Cognitive Modeling” Group led by Prof. Dr. Martin Butz invite applications for an open

PhD position (m/f/d; E13 TV-L, 65%, 3 years)

on the topic of compositional reasoning. From exploring variations of a musical motif to generating entirely new sentences or inventions, humans are able to leverage previously learned structures and generalize them to novel contexts. Our aim is to build computational models that capture the human ability to acquire and reuse compositional structures from experience, and apply these structures to
novel situations in a one-shot, goal-directed manner.

Potential topics include:

  • The role of inductive biases in inferring hidden structure from sparse examples
  • Adapting behavior to latent contexts through event-predictive cognition
  • Compositional Theory of Mind for decomposing the inferred goals of other agents and extracting individually relevant subgoals

in addition to the interests of the candidate.

About the position:

The candidate should hold a MSc degree in cognitive science, computer science, psychology, computational neuroscience, statistics, or a 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 programming languages (e.g., Python, R, Matlab, Javascript, Java, etc.), mathematics, 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 Cluster of Excellence “Machine Learning: New Perspectives for Science” and is embedded in the Tübingen AI Center, which is the highest ranked academic institution in artificial intelligence in the European Union. In addition, the position is also part of a network project within the ML cluster, providing a rich interaction structure with other researchers working on a similar topic, including members of the MPI Biological Cybernetics and MPI Intelligence Systems.

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 degreesas a single PDF to Charley Wu (charley.wu@uni-tuebingen[dot]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.

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.

Postdoktorandenstelle (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 positions have been filled.

Doktorandenstelle (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.