Opportunity: We invite applications for a PhD position with a strong background or interest in bioinformatics, big data analytics, machine learning, applied mathematics and its application in computational proteomics. The successful candidate will become a key member of an ERC Starting Grant funded project called ORIGIN which aims to answer a fundamental question in biology: To which extent and prevalence are isoforms translated and functionally relevant.
While mass spectrometry-based proteomics is the de-facto standard for measuring proteomes, it is not good at identifying isoforms. Proteins, thus also isoforms, leave a deterministic multi-dimensional fingerprint in each proteomic measurement. The central goal is to discover and quantify protein isoforms systematically by a novel MS-based proteomics data analysis strategy that utilizes these fingerprints. Candidates therefore must have a strong interest in one or more of the following aspects:
* Tap into the wealth of data the proteomics community has already amassed to train deep neural networks that allow the prediction of fingerprints.
* Implement an innovative data analysis strategy that utilizes the predictions to identify and quantify isoforms.
* Demonstrate that the novel approach can be used to address open questions in isoform-biology of varying biological and technical complexity.
The main work duties of the PhD are in research and assisting in the supervision of bachelor and master-level scientist.
Requirements: Candidates must hold an internationally recognized MSc degree in Bioinformatics, Biostatistics or a related discipline. Extensive theoretical knowledge of and practical skills in statistical analysis, data mining, data integration, machine learning, programming and database design are a plus. Additional desirable skills include a sound understanding of proteomic or related technologies as well as basic biological and (bio)chemical concepts. We are looking for a self-motivated and broadly interested individual with high potential and a strong sense of responsibility. Flexibility and the ability to work in a fast-paced environment on multiple scientific and infrastructure projects are essential. Good inter-cultural and interpersonal communication skills as well as presenting complex data to scientists in English are also important.
Our offer: The position is available for four years. You will join an interdisciplinary team of life scientists and bioinformaticians who use the latest proteomic approaches. The TUM is one of the best academic institutions in Germany, a well worked out international program, offers a stimulating work environment and excellent future perspectives.
Application process: Applicants should send a dossier containing a motivational statement (max. one page), a curriculum vitae summarizing qualifications and experience, copies of degrees and transcripts of study records, names and the email addresses of at least one referee as a single PDF document to Mathias Wilhelm (via mail mathias.wilhelm[at]tum.de). Online interviews will be conducted with selected candidates and remaining shortlisted candidates may be invited to the TUM campus in Freising, Germany, for face-to-face meetings with the group. All successful candidates are required to start June 1st, 2023.
Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Equal opportunity: The Technical University of Munich is an equal opportunity employer. As such, applications from women are explicitly encouraged. Preference will be given to candidates with disabilities who have essentially the same qualifications.
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