Postdoctoral researcher position Requisition No.: 303/2024

21 Feb 2024
Job Information

Organisation/Company

University of Potsdam, Faculty of Science, Department of Mathematics

Department

University of Potsdam, Faculty of Science, Department of Mathematics

Research Field

Computer science » Other
Mathematics » Applied mathematics

Researcher Profile

Established Researcher (R3)

Country

Germany

Application Deadline

29 Feb 2024 - 23:59 (Europe/Berlin)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

40

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

The DFG-funded Collaborative Research Center SFB 1294 “Data Assimilation – The Seamless Integration of Data and Models”, hosted at the University of Potsdam jointly with its partner Institutions HU Berlin, TU Berlin, WIAS Berlin, GFZ Potsdam, and TU Ilmenau invites applications for a

Postdoctoralresearcher position

Requisition No.: 303/2024

Our vision. The assimilation of time-dependent data sets into complex evolution models leads to unique mathematical and computational challenges. These challenges which provide the central theme of the SFB 1294. Data assimilation constitutes a rapidly expanding field at the confluence of several established research areas in mathematics, statistics, and machine learning, on the one hand and applications from the natural sciences and other disciplines. Our vision is to establish a rigorous mathematical underpinning of data assimilation, to develop principled computational methodologies, and to apply these methodologies to newly emerging application fields in the geosciences, neurosciences, pharmacology, and biophysics. The SFB 1294 provides an excellent research infrastructure including a large interdisciplinary network of researchers and its own graduate school, as well as funding opportunities for conference visits, summer schools, and hosting international experts etc.

The position. We seek applicants for a postdoctoral position (TVL - E13) within Project A03: “Sequential and adaptive learning under dependence and non-standard objective functions” from April 2024 (at the earliest) to June 2025 (PIs: Alexandra Carpentier / Jana de Wiljes). Applications will be accepted until February 29, 2024.

The project considers the problem of learning sequentially, adaptively and on the basis of partial information in an uncertain environment. In this setting, the learner sequentially and actively collects the data, which is not available beforehand, in a batch form. The objective of the recommendation system (learner) is to recommend at each time t an item (a set of actions) to a user that fits their needs. The recommendation system does not observe the preferences of the users, but only their opinions on what the recommendation system has recommended as items previously. This raises many interesting problems, for example, finding optimal sequential strategies that can rapidly single out the most liked items, or efficiently determining the preferences of users, etc. In many real-life cases, the collected data has dependencies, and the objectives of the learner can vary. In this project, we consider a setting where our aim is to design strategies to collect (or to sample) sequentially and adaptively the data so that it can be assimilated by the model in the most effective way possible. An important milestone that we achieved was to extend the bandit problem to a case where the samples produced by each arm were allowed to depend on each other, via a mixing assumption. Our aim in the next phase is to generalize the results of the first phase, targeting dependent and non-stationary bandit settings, to the case where the set of actions is continuous. Spatial and temporal dependencies and non-stationarities will interact, giving rise to new problems and challenges.

The candidates should have a Ph.D. in applied mathematics or theoretical computer science (related to theoretical statistics or theoretical machine learning). The ideal applicant has also experience with sequential methods and/or dependent data. The candidate must be able to communicate effectively in both written and spoken English. Workplace will be at the Department of Mathematics at the University of Potsdam.

The position is classified within remuneration group 13 of the collective wage agreement among the German federal states (“Tarifvertrag für den öffentlichen Dienst der Länder” – TV-L). The fixed term of employment is in accordance with Section 2 subsection 1 of the German Act on Fixed-Term Employment Contracts in Science and Academia (Wissenschaftszeitvertragsgesetz or WissZeitVG). At least one-third of working hours is available for in-depth academic work.

The University of Potsdam values the diversity of its community and pursues the goals of equal opportunity regardless of gender, nationality, ethnic and social origin, religion/belief, disability, age, and sexual orientation and identity. Applications from abroad and from persons with a migration background are expressly encouraged. The university strives for a balanced gender ratio in all employment groups; in areas where women are underrepresented, women are given preference in case of equal suitability (Section 7 paragraph 4 of the Brandenburg Higher Education Act). People with disabilities are given preferential consideration in case of equal suitability. In aptitude tests and selection interviews, individual compensation measures for disadvantages are granted, taking the specific disability into consideration. If a person with a disability would like to make use of individual compensation measures, please state this in the application letter.

If you completed higher education qualifications outside the EU, please submit a German translation and the assessment of the Central Office for Foreign Education (Zentralstelle für ausländisches Bildungswesen – ZAB) . Alternatively, please send us a PDF file from the database for the recognition and assessment of foreign higher education certificates (ANABIN) .

For more information about the CRC, please see our website: www.sfb1294.de . Please send your application (letter of motivation, CV, publication list; compiled in one PDF file) to [email protected] ). For specific queries on the position please contact Alexandra Carpentier (email: [email protected] ).

Requirements

Research Field

Computer science » Other

Education Level

PhD or equivalent

Research Field

Mathematics » Applied mathematics

Education Level

PhD or equivalent

Skills/Qualifications

The candidates should have a Ph.D. in applied mathematics or theoretical computer science (related to theoretical statistics or theoretical machine learning). The ideal applicant has also experience with sequential methods and/or dependent data. The candidate must be able to communicate effectively in both written and spoken English. Workplace will be at the Department of Mathematics at the University of Potsdam.

Languages

ENGLISH

Level

Excellent

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

University of Potsdam, Faculty of Science, Department of Mathematics

Country

Germany

City

Potsdam

Geofield

Where to apply

E-mail

[email protected]

Contact

City

Potsdam

Website

http://www.sfb1294.de

Street

Am Neuen Palais 10

E-Mail

[email protected]

STATUS: EXPIRED