For any questions, do not hesitate to ask:
Dr. Michael Bussmann Tel.: +49 3581 37523 11,
Mrs. Weronika Mazur Tel.: +49 3581 37523 23,
+49 171 3635554
Place of work:
Görlitz
Working hours:
39 h/week
Deadline:
31 March 2023
Online application
English / German
Job-Id: 2023/27 (1611)
At HZDR, we promote and value diversity among our employees. We welcome applications from people with diverse backgrounds regardless of gender, ethnic and social origin, belief, disability, age, and sexual orientation. Severely disabled persons are given preference in the event of equal suitability.
Helmholtz-Zentrum
Dresden-Rossendorf
Bautzner Landstraße 400
01328 Dresden
Postdoctoral Researcher (f/m/d) on Deep Learning Language Models of DNA
Through cutting-edge research in the fields of ENERGY, HEALTH and MATTER, Helmholtz-Zentrum Dresden-Rossendorf (HZDR) solves some of the pressing societal and industrial challenges of our time. Join our 1.500 employees from more than 50 nations at one of our six research sites and help us moving research to the next level!
The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. CASUS was founded in 2019 in Görlitz and conducts digital interdisciplinary systems research in various fields such as earth systems research, systems biology and materials research.
Natural Language Processing has substantially improved deep learning on language and our understanding on linguistics due to unprecedented possibilities for text analysis. In a collaboration between the TU Dresden and CASUS we use transformer based deep learning algorithms that treat genomes as text. The project will encompass the training of task-agnostic language models and use these to extract language rules and biological meaning, such as how genome stability is encoded in the genome.
To strengthen our diverse team, we are looking for a Postdoctoral Researcher (f/m/d) on Deep Learning Language Models of DNA. The position will be available from 01 April 2023.
The position is initially limited to three years. The position will be mainly located in Dresden (Germany), embedded in the team of Anna Poetsch at the Biotechnology Center of the TU Dresden and in close interaction with CASUS in Görlitz (Germany).
Your tasks:
- Programming of transformer based deep learning algorithms (in Python) on genomic data
- Data analysis of genomic data, attention, and learning parameters
- Design of deep learning tasks to interrogate questions of genome biology
- Collaboration in the research team on other questions of machine learning, functional genomics, genome instability
- Supervision of junior lab members
- Presentation and publication of results
Your profile:
- PhD degree at a relevant field, such as Molecular Biology, Computational Biology, Bioinformatics, Genetics, Computer Science, Mathematics, Linguistics, or equivalent scientific background
- Comprehensive experience with programming in python
- Experience in using machine learning algorithms
- Comprehensive knowledge of genome biology
- Experience in writing scientific publications
- Previous knowledge in DNA repair, genome (in)stability or cancer genomics or evolutionary genomics would be an asset
- Previous experience working in an international and interdisciplinary environment is a plus
- Knowledge of the German language is not required, but very good communication skills in English
Our offer:
- A vibrant research community in an open, diverse and international work environment
- Scientific excellence and extensive professional networking opportunities
- A wide range of qualification opportunities and individual career counseling provided by the Postdoc Center HZDR-TUD
- Salary and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund) including 30 days of paid holiday leave, company pension scheme (VBL)
- We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours
- Numerous company health management offerings
- Employee discounts with well-known providers via the platform Corporate Benefits
Kindly submit your completed application (including cover letter, CV, diplomas/transcripts, etc.) only via our Online-application-system.