PhD Position in Computational Biology

University of Bern Institute of Biochemistry and Molecular Medicine

PhD position

The Institute invites applications for a research and teaching PhD position (100%, 4 years).

The PhD candidate will develop his or her dissertation project within the field of Computational Biology.

The project

We are looking for a PhD candidate to work in the areas of machine learning, and protein modeling and design. Research objectives include the development and implementation of deep generative models for protein design with applications in the fields of antibody therapeutics and biosensor design. The research will be carried out in the group of Thomas Lemmin of the Institute of Biochemistry and Molecular Medicine (IBMM) at the University of Bern, in Bern, Switzerland.

The Ph.D. Position

The doctoral student will be enrolled in the Graduate School for Cellular and Biomedical Sciences (GCB). The doctoral student will work under the scientific supervision of Thomas Lemmin. The successful candidate will be offered the possibility to work in a dynamic research team and in a multidisciplinary and international scientific environment.

The PhD candidate will collaborate to the development of the institute research agenda. She or he will have the task of setting up a collection of data for his or her dissertation, while at the same time participating in a variety of tasks related to the research streams in which he/she is involved.

On the teaching side, she/he will work as teaching assistant in courses at either bachelor or master level, helping in the preparation of teaching materials and tutoring students. Fluent German is required for supervising bachelor level courses and laboratory practicals.

The PhD candidate is also asked to present papers at scientific conferences and produce publications for scientific journals.
Candidates' profile

You are a highly motivated individual capable of grasping and applying new concepts, working individually, and collaborating with multidisciplinary research teams.
• Master of Science (MSc) degree
• Interest in Machine Learning and/or Computational Biology. Proficiency in Deep Learning and Molecular Modeling are a plus.
• Good skills in oral and written English
• Fluent German is a requirement for teaching
• Ability to work independently and to plan and direct own work
• Motivation to engage in the elaboration of a PhD dissertation
• Ability to work in team and autonomy in scheduling research steps
• Interest for teaching and tutoring students and availability to collaborate with colleagues (engage in scientific dialogue, listen and think critically) are required
Contract terms

Admission to the Ph.D. program is highly competitive. Admission decisions are based on the candidate's background, interests, attitude and potential for academic achievement. Successful enrolment in the Ph.D. program and the position as doctoral researcher are not compatible with a further professional activity.

The successful candidates will work as research assistants at the Institute of Biochemistry and Molecular Medicine (IBMM), and will have the possibility to interact with an international network of collaborators.
General terms

Workplace is the University of Bern, located in Bern, Switzerland. Availability to travel to other parts of Switzerland and abroad (for purposes of collaboration and research) is required.

The position will be kept open until a suitable candidate has been found.
The Application

Applications should contain: (1) a letter in which the applicants describe their research interests and the motivation to apply, (2) a complete CV, (3) copies of relevant diplomas, certificates as well as the full transcript of records, (4) an electronic version of a research work (Master thesis or other scientific publication). The latter must be accompanied by a short summary in English (1 page maximum). A support letter written by the Master thesis supervisor (or another Professor who knows the candidate well) is equally welcome. (5) letter / contact information of 2 – 3 references.

Please send your application in electronic form or requests for further information to Successful applicants will be invited to discuss with our group and visit our lab.

As an institute that values diversity, we particularly encourage applications from women and from all individuals from underrepresented groups.