15 Fully funded PhD studentships in Quantitative Biology
The advent of large-throughput data is transforming life sciences into an increasingly quantitative discipline. The University of Lausanne (Switzerland) is at the forefront of this revolution, with quantitative research ramping up throughout the Faculty of Biology and Medicine, a dedicated department of Computational Biology, and interdisciplinary units such as the Center for Integrative Genomics. UNIL also hosts the headquarters of the Swiss Institute of Bioinformatics, to which many quantitative research groups are affiliated, and closely collaborates with EPFL on the same campus. Ideally situated along the lake of Geneva, near Lausanne's city center, UNIL brings together over 120 nationalities.
UNIL's Faculty of Biology and Medicine has a recently launched a doctoral programme entitled "Quantitative Biology". A wide range of research groups are recruiting PhD students, covering areas as diverse as evolution, synthetic biology, plant science, cancer genomics, microbiology, molecular biology, neuroscience, biological imaging, and computational biology.
Hiring principal investigators include Roman Arguello, Richard Benton, Sven Bergmann, Giovanni Ciriello, Adrien Depeursinge, Paul Franken, Maria-Cristina Gambetta, Jerome Goudet, Laurent Keller, Zoltan Kutalik, Liliane Michalik, Serge Pelet, Alexandre Reymond, Marc Robinson-Rechavi, Sebastian Soyk, Yuko Ulrich & Jolanda van Leeuwen.
- Expected start date: 01.03.2020 or to be agreed
- Contract length: The initial contract is for one year and is extendable to a total of 4-5 years.
- Activity rate: 80-100%
- Workplace: University of Lausanne, Dorigny, Switzerland
We are accepting applications from talented and enthusiastic candidates who are interested in a dynamic, well-supported lab at a top research institution. Candidates need to finish a Master's degree in a relevant area before the start date of their doctoral studies.
We are looking for three main types of PhD students:
- Students with a life science degree, interested in working in an experimental lab, but with a high degree of motivation to learn the fundamentals of computational biology, and to develop quantitative skills to analyse data more effectively
- Students with a life science degree interested in working in a dry computational lab, keen to deepen their quantitative skills and broaden their horizon in terms of experimental and computational techniques
- Students with a non-biological background (e.g. computer science, maths, physics), who are highly motivated to transition to Life Sciences
A high level of written and spoken English proficiency is required since most scientific activities are conducted in English.
What the position offers you
You will develop your research project while working in a world competitive, interdisciplinary and highly collaborative environment.
The PhD programme in Quantitative Biology provides opportunities for professional training and acquisition of highly transferable skills. This is complemented by a wide range of activities (retreats, symposia, student life).
The positions are fully funded. Salary and benefits are internationally highly competitive. Additional funding for consumables, computing, and to attend international conferences is available.
Prof. Christophe Dessimoz, Director of the UNIL Doctoral Programme in Quantitative Biology program firstname.lastname@example.org
Please, submit your full application in Word or PDF at the URL
by 15 October 2019.
Your application should include:
- Cover letter, including research interests and motivation to join the programme
- Curriculum vitae including, if available, extracurricular activities, internships, publications, conferences, awards, software contributions, etc.
- Master's thesis summary (max. one page)
- The names and contact details of 2-3 reference
- The name of preferred host laboratories (this is only indicative and can still change at the interview stage)
Lab visits and interviews will take place on 3-4 December 2019 in Lausanne.
For more information, please consult http://unil.ch/quantitative-biology