Research Associate for the Project “PUNCH4NFDI” Machine Learning in Particle- and Astrophysics § 28 Subsection 3 HmbHG

Registration website

Institution

Faculty of Mathematics, Informatics and Natural Sciences, Department of Physics, Institute of Experimental Physics

Salary level

EGR. 13 TV-L

Start date

01.02.2022, fixed until 30.09.2026 (This is a fixed-term contract in accordance with Section 2 of the academic fixed-term labor contract act [Wissenschaftszeitvertragsgesetz, WissZeitVG]).

Application deadline

28.11.2021

Scope of work

full-time position suitable for part-time

Responsibilities

Duties include academic services in the project named above. Research associates may also pursue independent research and further academic qualifications.

Specific Duties

The PUNCH4NFDI consortium aims at a sustainable utilisation of research data and the establishment of a FAIR data management for particle physics, astroparticle physics, astronomy, and hadron&nuclear physics. In doing so, the consortium builds especially on unique expertise in "big data" management, in "open data" and in data transformations. The consortium, which is part of the German national research data infrastructure (Nationale Forschungsdateninfrastruktur, NFDI) represents more than 40 institutions - university institutes, Max Planck institutes, Helmholtz centres, as well as Leibniz institutes.

Modern tools of machine learning and deep learning are quickly becoming indispensable for experimental particle physics, astronomy, and other domains of fundamental physics. The large data volumes produced by future runs of e.g. the Large Hadron Collider (LHC) or the Square Kilometer Array (SKA) lead to novel challenges in scaling up model training and inference to exascale datasets. At the same time, similarities in workflows and data structures offer the potential for shared algorithms and data processing setups.

We invite applications for a research associate position on the topic of deep learning in particle- and astrophysics. Possible topics include:

• development of automated machine learning methods for fundamental physics
• research into foundational models for transfer learning
• development of machine learning technique for large, distributed datasets

Depending on the primary focus of activities, the work will take place embedded in the group of Prof. Kasieczka on Campus Bahrenfeld or in the the group of Prof.

Brüggen at Hamburg Observatory. In both cases, close collaboration and frequent exchange locally and also within the larger NFDI effort are foreseen.

Requirements

A university degree in a relevant field plus doctorate.

Excellent English communication skills are required. We expect candidates to be experienced in programming, work successfully in a team environment, and show excellent initiative and engagement.

Outstanding candidates will have prior knowledge in the development and application of deep learning using modern software packages as well as relevant domain expertise in either particle physics or astrophysics.

We offer

• Reliable remuneration based on wage agreements
• Continuing education opportunities
• University pensions
• Attractive location
• Flexible working hours
• Work-life balance opportunities
• Public transport pass (ProfiTicket) and much more
• Health management
• Educational leave
• 30 days of vacation per annum

As a University of Excellence, Universität Hamburg is one of the strongest research universities in Germany. As a flagship university in the greater Hamburg region, it nurtures innovative, cooperative contacts to partners within and outside academia. It also provides and promotes sustainable education, knowledge, and knowledge exchange locally, nationally, and internationally.

The Free and Hanseatic City of Hamburg promotes equal opportunity. As women are currently underrepresented in this job category at Universität Hamburg according to the evaluation conducted under the Hamburg act on gender equality (Hamburgisches Gleichstellungsgesetz, HambGleiG), we encourage women to apply for this position. Equally qualified and suitable female applicants will receive preference.

Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.

Tips on applying
Contact

Prof. Gregor Kasieczka

[email protected]

+49 40 8998-2123

Prof. Marcus Brüggen

[email protected]

+49 40 42838-8537

Reference number
368

LocationLuruper Chaussee 149

22761 Hamburg
To Google Maps

Application deadline
28.11.2021

Applications should include a cover letter, a tabular curriculum vitae, and copies of degree certificate(s). Please send applications by email to: [email protected]

More information on data protection in selection procedure.