The University of Copenhagen invites applications for a Postdoctoral fellow as part of two ongoing European projects – FindingPheno and FARM-CARE. FindingPheno is an EU Research and Innovation Action consisting of an international consortium of 5 research institutions and 3 industrial partners, Denmark – Apr 2022
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Position: Postdoctoral Fellow
No. of Positions: 1
Research Field: Bioinformatics, Computational Biology, Computer Science, Data Science, Mathematics, Statistics
Deadline to Apply: Expired
Joining Date: Jun 01, 2022
Contract Period: 3 Years
Salary: According to standard norms
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- PhD degree or equivalent doctorate, with a background in one or more of the following areas: statistics, data science, statistical genetics, computational biology, bioinformatics, computer science, and/or mathematics.
- Demonstrate a working proficiency in one or more programming languages commonly used in data science (e.g. Python, R, C/C++, Java or Julia) and have experience in the UNIX operating environment, and cluster computing.
- Fluency in English.
Other qualifications, not mandatory but of considerable interest:
- Previous experience or strong interest in working with large scale biological data such as genomics, metagenomics, multi-omics, etc.
- Experience with high-performance computing clusters/systems
- Experience with compiling and working with data from different sources
- Understanding of FAIR data principles, interest in Open Data
- Interest in scientific communication and/or public outreach
Statistical learning as a tool to understand host-microbiome interactions in health and disease
University of Copenhagen, as part of two ongoing European projects - FindingPheno and FARM-CARE. FindingPheno is an EU Research and Innovation Action consisting of an international consortium of 5 research institutions and 3 industrial partners. Further information on FindingPheno can be found at www.findingpheno.eu. The goal of the project is to develop statistical and machine learning tools to use multi-omics data to better understand host-microbiome interactions.We aim to go beyond genotype-phenotype associations to reveal causal pathways. FARM-CARE is a project funded by the Joint Programming Initiative on Antimicrobial Resistance (JPIAMR) to control spread of antimicrobial resistance using different approaches including machine learning.
The candidate will be advised by Assoc. Prof. Shyam Gopalakrishnan, who leads the FindingPheno project based at the Center for Evolutionary Hologenomics (https://ceh.ku.dk). The Gopalakrishnan research group focuses on using population and statistical genetics to understand genotype-phenotype associations with a special focus on the role of microbiomes in evolutionary processes.The candidate will also work closely with Prof. Luca Guardabassi, based at the Section for Veterinary Clinical Microbiology at the Department of Veterinary and Animal Sciences. Prof. Guardabassi leads the One Health Antimicrobial Resistance (OHAR) research group, the focus of which is to discover innovative solutions for improving diagnosis and treatment of bacterial infections in animals.
The candidate will compile, engineer and analyse a collection of large publicly available and project-specific multi-omics datasets, which include whole genomes, metabarcodes/metagenomes, transcriptomes, metatranscriptomes, proteomes, extensive phenotyping and metadata. These datasets span multiple species such as chicken, salmon, honey bee, tomato and pig.
The first part of the project will focus on performing exploratory analyses to understand the relationship between host genomic processes and microbiome variations that have a significant impact on plant and animal phenotypes, with a particular focus on host-microbiome interactions.Subsequently, statistical and machine learning models developed in FindingPheno will be applied to the various datasets to better understand the biological mechanisms and pathways leading from host-microbiome-environment interactions to organismal phenotypes.Finally, the candidate will work closely with statisticians and data scientists in several research groups to help develop and improve machine learning and computational tools to incorporate multi-omics data into a coherent inference framework for host-microbiome interactions.
As part of the two projects, FindingPheno and FARM-CARE, the candidate will be working in a truly interdisciplinary, multicultural research environment, and will interact with several research groups spread across the globe.The candidate will have an opportunity to interact with scientists at different career stages in research groups in Finland, Hungary, Portugal, England, Germany, Ireland, and Colombia. Teamwork and collaboration will be important skills; however, the candidate will also be given ownership over their own research project and deliverables.
The fully funded postdoctoral fellowship will be hosted at the Section for Hologenomics/Center for Evolutionary Hologenomics at the GLOBE Institute, and Section for Veterinary Clinical Microbiology at the Department of Veterinary and Animal Health. The candidate will have the opportunity to collaborate with leaders in the fields of world leading experts in population genetics, statistical genetics, computational biology, clinical microbiology, archaeology, evolutionary genomics, and many other related fields of research.The University of Copenhagen is a world-leading institution of higher learning and provides excellent programs in genetics, archaeology, statistics, computer science and mathematics.
How to Apply?
Application Method: Online Application
Ref. No.: -
Your online application must be submitted in English by clicking ‘Apply now’ below. Furthermore your application must include the following documents/attachments – all in PDF format:
- Motivated letter of application (max. one page).
- CV incl. education, work/research experience, language skills and other skills relevant for the position.
- A certified/signed copy of a) PhD certificate and b) Master of Science certificate (if applicable), c) transcript of records, including courses followed and marks obtained. If the PhD is not completed, a written statement from the supervisor will do.
- List of publications.
Application deadline: 6 April 2022, 23.59pm CETWe reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.
The further process
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.
You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.
Note or Other details
Salary and terms of employment
The successful applicant will be hired as postdoctoral fellow for a 3-year period from 1 June 2022.
Salary, pension and terms of employment will be in accordance with the agreement between the Danish Ministry of Finance and AC (Danish Confederation of Professional Associations).Currently, the monthly salary starts at 35,000 DKK/approx. 4,700 EUR (October April 2022 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 17.1 % to your pension fund.
Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.
The position is covered by the Job Structure for Academic Staff at Universities 2020.
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For further information please contact Assoc. Prof. Shyam Gopalakrishnan: [email protected].If you consider applying from abroad, you may find useful information on how it is to work in Denmark and at UCPH at these links:https://ism.ku.dk/https://ivh.ku.dk https://www.nyidanmark.dk/en-GBhttps://www.workindenmark.dk/
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