Postdoctoral researcher in mathematical phylodynamics
The Computational Evolution Group, led by Prof. Dr. Tanja Stadler, in the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zurich works at the interface of mathematics, computer science and evolutionary biology. We develop phylogenetic and phylodynamic methods to understand evolutionary, ecological, epidemiological and developmental processes on different scales based on genetic data.
Our research group is located in Basel, Switzerland’s oldest university city and a European hot-spot for biomedical research. Our department is in close proximity to several other academic research institutes as well as major pharmaceutical and biotech companies. We are also part of the Swiss Institute of Bioinformatics, a major developer and provider of bioinformatics services and resources.
Applications are invited for the position of postdoctoral researcher with Prof. Dr. Tanja Stadler. The position is fixed-term for 2 years with possibility of extension.
Project background
How did the current biodiversity emerge? How does a single fertilised egg develop into a functioning organism? Which factors govern the spread of a pathogen during an epidemic? The answers to these questions depend on the underlying population dynamic processes, i.e. the replication and change of individuals. Within the EU-funded PhyCogy project (https://cordis.europa.eu/project/id/101001077 ; ERC consolidator grant), we strive to formulate and characterise models describing the replication and change of individuals. This project aims to generalize these so-called phylodynamic models into a coherent framework, which will be applied within the ERC project to answer questions like those above. Applications span the fields of macroevolution, epidemiology, and developmental biology. The generalisability of the developed framework will enable future application across biological scales in areas like microbiology, virology, ecology, immunology, and cancer research.
Job description
The open position entails working closely with Prof. Dr. Tanja Stadler and other team members in the Computational Evolution group on mathematical models for phylodynamics. The overarching goal is to develop a general coherent phylodynamic framework allowing us to identify fundamental population dynamic rules across biological scales based on both phylogenetic trees and data on the abundance of individuals.
The initial goal is to explore characteristics, similarities and limitations of the stochastic birth-death model and the coalescent within phylodynamics. Based on these insights, you will formulate a neutral phylodynamic model that has these common birth-death-based and coalescent-based phylodynamic models embedded within it. Subsequently, the neutral phylodynamic model will be extended such that population structure, selection and cell differentiation can be taken into account. We envision that the resulting model will be the basis for future phylodynamic applications.
You will work on the mathematical aspects of the models. Within the ERC team, the mathematical insights will be employed by group members in computational tools (such as BEAST2) and applied to real-world data.
We offer
We offer a dynamic and supportive working environment with flexible working hours. ETH Zurich is a family-friendly employer with excellent working conditions and offers highly competitive salaries . The position also comes with funding to attend international conferences and workshops and you will have the opportunity to participate in personal growth and career development opportunities offered by ETH Zurich and the Swiss Institute of Bioinformatics. Switzerland offers top quality of life – including beautiful natural scenery and fantastic infrastructure. We look forward to showing you why Basel, a very international small city ranked the tenth most livable city in the world by Mercer, is a great place to live and work!
Your profile
We are looking for a highly motivated early career researcher with strong quantitative skills. You will have completed a PhD in mathematics, biostatistics, statistics, physics or a related discipline prior to starting the position. Experience with phylogenetics or phylodynamics is beneficial, but not a requirement for the position. You will engage in interdisciplinary research as part of a team, so clear and effective communication skills are a priority. We value an open and inclusive group culture. As a member of the Computational Evolution group, you will be expected to help us maintain a positive team dynamic and a welcoming work environment. Our working language in the group is English and no knowledge of German is required. In line with our commitment to an open and inclusive group culture we welcome applications from individuals of all demographic groups and personal backgrounds.
About ETH Zürich
ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.
Curious? So are we.
We look forward to receiving your online application with the following documents:
- Curriculum Vitae including your educational history and full list of publications.
- Letter of motivation of max. 2 pages covering your past research experiences and future research interests, goals and how they would relate to and fit in with the PhyCogy project and the Computational Evolution group’s research domain and activities.
- Names, e-mail addresses, and phone numbers of at least two references, mentioning for each the professional relationship you have with them.
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. We will review applications as they come in, until the position is filled.
For further information please visit our lab website at https://bsse.ethz.ch/cevo . Questions regarding the position (no applications) should be directed to Dr. Louis du Plessis ([email protected] ).
Similar Positions
-
Postdoc Position In Experiment Guided Computational Neuroscience , ETH Zurich, Switzerland, 1 day ago
100%, Zurich, fixed-term The Laboratory of Biosensors and Bioelectronics (LBB) is looking for a postdoc who would lead our computational efforts towards understanding fundamental neuroscience conc...
-
Postdoc On Resilience Of Forests To Air Pollution And Climate Extremes , ETH Zurich, Switzerland, 1 day ago
100%, Zurich, fixed-term The Grassland Sciences group is a vibrant and international working group at the Department of Environmental Systems Science at ETH Zurich. We are looking for a reliable, ...
-
Postdoctoral Researcher In Generative Ai For Mechanism Design , ETH Zurich, Switzerland, 1 day ago
100%, Zurich, fixed-term Are you a highly motivated and enthusiastic researcher looking to make a difference in the field of AI applied in Healthcare? Join us at the Spinal Cord Injury Artificial ...
-
Two Postdoctoral Positions In The Electrochemical Energy Systems Laboratory , ETH Zurich, Switzerland, 1 day ago
100%, Zurich, fixed-term The Electrochemical Energy Systems Laboratory in the Department of Mechanical and Process Engineering at ETH Zurich is inviting applications for two postdoctoral positions...
-
Research Assistant Architecture And Urban Design , ETH Zurich, Switzerland, 1 day ago
60%, Zurich, fixed-term The Chair of Architecture and Urban Design Prof. Hubert Klumpner, Department of Architecture is looking for an Architect to collaborate as Research Assistant within teachi...
-
Doctoral Researcher In Dynamic Stochastic Learning Of Train Dynamics As Enabler To Highly Automated Train Operation , ETH Zurich, Switzerland, 1 day ago
100%, Zurich, fixed-term This project aims at developing a parsimonious and accurate dynamic model of train motion, with values calibrated from real life measurement of different sensor types; exp...