Tenure Track Professorship for Computational Psychiatry (W1 Tenure Track to W2)

The Faculty of Medicine invites applications for a

Tenure Track Professorship for Computational Psychiatry (W1 Tenure Track to W2)

at the Department of Psychiatry and Psychotherapy, to be filled at the earliest possible date. This professorship is funded by the Tenure Track Programme of the German Federal Government and the Federal States and is initially limited to six years.
The Philipps University of Marburg strengthens the area of theoretical and computational neurosciences by strate-gically filling several professorships and a junior research group.
The research focus of the professorship “Computational Psychiatry” is the analysis and evaluation of multidimen-sional, longitudinal data (“Multi-Omics”), in healthy probands and in patients with mental disorders with a focus on magnetic resonance imaging (MRI). The professorship is to be located at the interface between methodically oriented developments of machine learning algorithms, applied to MRI data, and, possibly, behavioural parameters, genomics, proteomics, metabolomics and clinical-translational research. Participation in the university’s research networks in the fields of clinical and systems neuroscience as well as active participation in new research initiatives is expected, in particular participation in the DFG research group 2107 “Neurobiology of affective disorders. A translational perspective on brain structure and function”. The professorship will be involved in research and teaching.
The Dept. of Psychiatry has a core facility with a 3 T MRI scanner for neuroscientific research, staffing for its operation, and the corresponding hardware and software. Further core facilities are available (www.uni- marburg.de/fb20/forschung/corefacilities). The Dept. of Psychiatry has a laboratory for molecular neurobiology. We offer excellent opportunities for scientific collaboration at the Centre for Mind, Brain and Behaviour (CMBB) jointly with the Faculties of psychology, medicine, mathematics, computer science and physics. The Dept. of Psychiatry is, among others, involved in SFB/TRR 135, IRTG 1901, BMBF ProtectAD, BMBF BipoLIFE, in the master’s programs “neurosciences” and in the interdisciplinary research priority on “neurosciences” of the faculty of medicine and the university.
Applicants must have completed a degree in neuroscience, medicine, psychology, physics, biology, computer science, data science, or a similar subject, and must have experience as a postdoc. Interdisciplinary experience in the area of machine learning in mental disorders (depression, schizophrenia, bipolar disorder, anxiety disorders) is an advantage.
This call is explicitly aimed at researchers (m/f/d) in the early stages of their scientific careers. The duration of the employment in research and science after obtaining the doctoral degree should not exceed four years (or seven years for physicians). Furthermore, applicants should not have received their doctorate at the University of Marburg. In the case that the doctoral degree was obtained at the University of Marburg, the applicant should have worked in research and science outside of the University of Marburg for at least two years thereafter (in accordance with § 64 Abs. 3 Hessisches Hochschulgesetz HHG, the State of Hessen Higher Education Act). We are looking for a researcher with outstanding initial scientific achievements and an innovative scientific profile that demonstrates potential for a successful future career in science at the highest international level.
The employment requirements of §§ 61, 62 and especially 64 HHG apply. The Tenure Track professorship is initially a grade W1 fixed term (6 years) position. If the requirements under general German civil service law are met, the applicant shall be granted a temporary civil service status for a period of six years. In the event of a positive evaluation of professional, pedagogical and personal aptitude, the applicant will be granted a civil service status for life, combined with the assignment of a W2 permanent professorship. Further information on tenure track professorships at the University of Marburg is available at https://www.uni-marburg.de/de/universitaet/ pro-fil/berufungskultur/tenure-track.
The Universities of Giessen and Marburg have founded a research alliance with the TH Mittelhessen University of Applied Sciences (the Research Campus Central Hessen), within the scope of which the two medical faculties of Giessen and Marburg practice a structured cooperation based on coordinated priorities. Applicants are therefore expected to be willing to cooperate across universities and faculties and to participate in joint projects.
The University of Marburg attaches great importance to the intensive supervision of students and doctoral candi-dates and expects from its lecturers and thus from the applicants a distinctive presence at the university, a high degree of commitment in the field of academic teaching and an intensive participation in the planned further development of medical education.
We support women and therefore explicitly encourage them to apply. We welcome individuals with children – the University of Marburg is committed to the goal of a family-friendly university. People with disabilities in the terms of the SGB IX (§ 2 Abs. 2, 3 SGB IX) are preferred if they are equally qualified for the position. Application and interview costs will not be reimbursed.
Please send your application documents (copies) including a research and a teaching concept using the appli-cation form provided on http://www.uni-marburg.de/de/fb20/fachbereich/services/formulare to the President of the University of Marburg, Biegenstraße 10, 35032 Marburg, Germany, by October 30th 2020, stating your business and private address. In addition, applications in a PDF file can be sent to bewerbung@verwaltung.uni- marburg.de.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.