Stellenausschreibungen

Aktuell sind mehrere Stellen zu besetzen.

DoktorandIn (E13 TV-L, 65%) - Machine Learning in Translational Single Cell Biology

 

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

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

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

The available position focuses on developing and applying machine learning methodology to high dimensional, spatial proteomic/transcriptomic single-cell data in translational research in oncology, immunology and infectiology. Specifically, we plan developing a combination of mechanistic and machine learning models for spatial and temporal dynamics of healthy and pathological differentiation processes driving success or failure  of immunotherapies in 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 and single-cell biology 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 such as but not confined to the Clusters of Excellence of Machine Learning and Image-Guided and Functionally Instructed Tumor Therapies with state-of-the-art infrastructure, providing the successful applicant with unique opportunities to develop a strong interdisciplinary portfolio in machine learning and translational single-cell 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 http://www.imsb.ethz.ch/. 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.

Fremdsprachensekretär:in (m/w/d, E 9a TV-L, 50%)

Der Fachbereich Informatik der Mathematisch-Naturwissenschaftlichen Fakultät, Universität Tübingen, sucht zum nächstmöglichen Zeitpunkt eine/n

Fremdsprachensekretär:in (m/w/d, E 9a TV-L, 50%)

Die Stelle ist unbefristet zu besetzen.

Das Aufgabengebiet umfasst die selbstständige Korrespondenz (überwiegend in Englisch und Französisch) mit (inter)nationalen Wissenschaftler:innen, die Betreuung von in- und ausländischen Mitarbeiter:innen und Gast-wissenschaftler:innen sowie die Mitwirkung bei der Organisation und Durchführung von Konferenzen mit in- und ausländischen Teilnehmer:innen, außerdem die Bewirtschaftung von Drittmitteln, die Organisation der Einschreibung von internationalen Doktorand:innen oder Post-Docs und vielfältige allgemeine Sekretariatsaufgaben wie Organisation von Terminen und Sitzungen, Verwaltung von Unterlagen einschließlich bibliographischer Datenbanken, Unterstützung bei der Beantragung von Fördermitteln (Verwaltung von Formularen und Anträgen).
Vorausgesetzt wird eine Ausbildung im Bereich Fremdsprachensekretariat mit den Sprachen Englisch und Französisch oder vergleichbare nachgewiesene Kenntnisse. Gute Kenntnisse im Umgang mit Office- und Internetanwendungen werden ebenso vorausgesetzt. Erwartet werden sowohl die Fähigkeit zu selbständiger Arbeit als auch zur Arbeit nach Vorgaben, Zuverlässigkeit, Engagement, Kommunikationsfähigkeit sowie Flexibilität und die Bereitschaft, sich in Neues einzuarbeiten.

Schwerbehinderte werden bei gleicher Eignung bevorzugt berücksichtigt.

Es besteht die Möglichkeit, die Position mit einer anderen derzeit ausgeschriebenen Stelle zu einer Anstellung in Vollzeit zu kombinieren.

Ihre Bewerbung mit den üblichen Unterlagen in englischer Sprache schicken Sie bitte als eine einzige PDF-Datei bis zum 31. Januar 2021 an die Geschäftsstelle des Exzellenzclusters für Maschinelles Lernen (E-Mail: ml-in-sciencespam prevention@uni-tuebingen.de).

Die Einstellung erfolgt durch die Zentrale Verwaltung.
 

Studentische Hilfskraft

Die Sprecher des Exzellenzclusters „Maschinelles Lernen – Neue Perspektiven für die Wissenschaft“ an der Universität Tübingen suchen zum nächstmöglichen Zeitpunkt eine

___________________________________________________________________
Studentische Hilfskraft
___________________________________________________________________

für die Unterstützung bei der Öffentlichkeitsarbeit des Exzellenzclusters auf verschiedenen Kanälen.

Aufgaben:
•    Unterstützung beim Aufbau und Betrieb eines Blogs für den Exzellenzcluster (inhaltliche Themenrecherche und
      redaktionelle Begleitung bei der Veröffentlichung von multimedialen Beiträgen; ggf. Bearbeitung eigener Beiträge)
•    Recherche weiterer Social Media-Kanäle für den Exzellenzcluster, welche insbesondere die Zielgruppe der
      Studentinnen und Studenten erreichen sollen
•    Unterstützung bei der Durchführung von digitalen Live-Formaten (z. B. Jahreskonferenz des Exzellenzclusters)
•    Korrekturlesen englischer Texte

Qualifikationen:
•    Fortgeschrittenes Bachelor- oder Masterstudium, bevorzugt in der Informatik oder den Medienwissenschaften
•    Verhandlungssichere deutsche und englische Sprachkenntnisse
•    Kenntnisse mit Programmen zur Bildbearbeitung (Photoshop) und Social Media-Kanälen.
•    Verfügbarkeit für mindestens zwei Semester (gerne länger)
•    Ausgeprägte Kommunikations- und Sozialkompetenz
•    Zuverlässige Arbeitsweise, Teamfähigkeit und organisatorisches Geschick

Beginn, Umfang, Dauer: Sobald wie möglich, spätestens Jan/Feb 2021, 40 Stunden im Monat für zunächst 12 Monate (mit Verlängerungsoption).

Vergütung: 10,63 € pro Stunde ohne Abschluss, 12,36 € pro Stunde mit Bachelorabschluss, 16,79 € pro Stunde mit Masterabschluss, Diplomabschluss oder äquivalenter Qualifikation.

Die Einstellung erfolgt bei Prof. Ulrike Luxburg. Bei Interesse richten Sie Ihre Bewerbung (mit Anschreiben, Lebenslauf und Studienleistungen) bitte möglichst in einer pdf-Datei an: sebastian.schwenkspam prevention@uni-tuebingen.de (Rückfragen bitte ebenfalls an diese Adresse). Als Referenz bitte angeben "GF_01".

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]

DoktorandIn oder PostdoktorandIn (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.

We are already in the processing of screening applications, please do not apply for the position any more.

[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.]

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