Computational researcher / PhD trainee wanted at the Center for Health Data Science
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København N
Faculty of Health and Medical Science
University of Copenhagen
The Center for Health Data Science (HeaDS), Faculty of Health and Medical Science, University of Copenhagen has an opening for a junior data scientist interested in health data science, bioinformatics and generative machine learning. The contract will cover 4 (1+3) years of employment, the first year as a research assistant, followed by a 3 year PhD fellowship within the field of health data science. The start date is 5th of August 2024 or as soon as possible.
About the Center for Health Data Science
The Center for Health Data Science (HeaDS) is a young, growing center that aims to strengthen data science skills at KU’s faculty of Health and Medical Science. The Center is made up of a well-connected research environment supported by several grants, the SUND Data Lab which provides data science support to researchers at the faculty, and a training infrastructure unit developed within the national Health Data Science Sandbox project. Our philosophy is a relaxed work environment driven by inspired and independent people.
The position
The three sections of HeaDS collaborate closely, and the advertised position connects you with all three sections of the Center, allowing you to expand your data science skills and prep you for a successful PhD using machine learning techniques within the field of health data science.
In the first year as a research assistant, you will join the SUND Data Lab, which provides data science support for SUND research groups and runs courses to improve the data science skills of the biomedical researchers. Concurrently, you will participate in the launch of a new research project supervised by Anders Krogh and Jennifer Bartell. This project has grown out of the Health Data Science Sandbox, a national computing infrastructure project developing training and research resources on academic HPCs.
The overarching aim of the research project (and the PhD traineeship) is to develop and test new methods for creating synthetic health datasets that can be used to support projects in precision medicine, health IT, and AI methods development. Synthetic health datasets are generated datasets that should capture the complex patterns of real, restricted-access clinical datasets via deep learning, yet pose minimal risk to patient privacy. The PhD traineeship will be a part of an NNF-funded collaboration with researchers from Aalborg University at the Center for Clinical Data Science and the Department of Law, and include interaction with the established Sandbox network. Together we aim to develop synthetic health datasets via benchmarked generative AI workflows, privacy metrics based on Bayesian statistics, and a framework for GDPR compliance of the developed methods.
Your profile
We’re looking for someone who wants to conduct innovative and impactful work at the crossroads of clinical data science, bioinformatics and deep generative modeling – HeaDS has a history of success with such interdisciplinary research projects and we hope you are excited to take on this challenge.
Position requirements
Desirable skills / interests
Valued personal competencies
Expectations as an RA/PhD student
For further information regarding the position, please contact specialkonsulents Jennifer Bartell ([email protected]) or Thilde Terkelsen ([email protected]). Please apply even if you don’t have experience with any of the ‘desirable skills’ – above all, we are looking for a curious and motivated candidate with a solid computational foundation that they are excited to build on.
Terms of Employment
The successful candidate will be offered a full-time position for a total of 4 years – the first year as research assistant and the following 3 years as PhD student, and employment is governed by the Protocol on PhD Research Fellows signed by the Danish Ministry of Finance and AC (the Danish Confederation of Professional Associations). The transfer to employment as a PhD student after the first year is conditioned upon a positive assessment of the candidate’s research performance during the first year as well as acceptance of enrolment in the Graduate School at the Faculty of Health and Medical Sciences.
How to apply
Your online application must be submitted in English by clicking ‘Apply now’ below. The application must include:
Application deadline: 12 May 2024 at 23:59 CEST.
Please note that only applications submitted before the deadline and consisting of the above listed documents will be considered. Applications will be reviewed on a running basis, and those received after the deadline will not be taken into consideration.
Info
Application deadline: 12-05-2024
Employment start: 05-08-2024
Working hours: Full time
Department/Location: Center for Health Data Science, SUND, KU
Kilde: Jobnet.dk
University of Copenhagen
The Center for Health Data Science (HeaDS), Faculty of Health and Medical Science, University of Copenhagen has an opening for a junior data scientist interested in health data science, bioinformatics and generative machine learning. The contract will cover 4 (1+3) years of employment, the first year as a research assistant, followed by a 3 year PhD fellowship within the field of health data science. The start date is 5th of August 2024 or as soon as possible.
About the Center for Health Data Science
The Center for Health Data Science (HeaDS) is a young, growing center that aims to strengthen data science skills at KU’s faculty of Health and Medical Science. The Center is made up of a well-connected research environment supported by several grants, the SUND Data Lab which provides data science support to researchers at the faculty, and a training infrastructure unit developed within the national Health Data Science Sandbox project. Our philosophy is a relaxed work environment driven by inspired and independent people.
The position
The three sections of HeaDS collaborate closely, and the advertised position connects you with all three sections of the Center, allowing you to expand your data science skills and prep you for a successful PhD using machine learning techniques within the field of health data science.
In the first year as a research assistant, you will join the SUND Data Lab, which provides data science support for SUND research groups and runs courses to improve the data science skills of the biomedical researchers. Concurrently, you will participate in the launch of a new research project supervised by Anders Krogh and Jennifer Bartell. This project has grown out of the Health Data Science Sandbox, a national computing infrastructure project developing training and research resources on academic HPCs.
The overarching aim of the research project (and the PhD traineeship) is to develop and test new methods for creating synthetic health datasets that can be used to support projects in precision medicine, health IT, and AI methods development. Synthetic health datasets are generated datasets that should capture the complex patterns of real, restricted-access clinical datasets via deep learning, yet pose minimal risk to patient privacy. The PhD traineeship will be a part of an NNF-funded collaboration with researchers from Aalborg University at the Center for Clinical Data Science and the Department of Law, and include interaction with the established Sandbox network. Together we aim to develop synthetic health datasets via benchmarked generative AI workflows, privacy metrics based on Bayesian statistics, and a framework for GDPR compliance of the developed methods.
Your profile
We’re looking for someone who wants to conduct innovative and impactful work at the crossroads of clinical data science, bioinformatics and deep generative modeling – HeaDS has a history of success with such interdisciplinary research projects and we hope you are excited to take on this challenge.
Position requirements
- MS degree in computer science, bioinformatics, biostatistics, or a field of science relating to data science (equivalent to a 2-year Danish master degree - for information on degrees already assessed, please see here or here)
- Programming skills in Python and familiarity with Linux
- Interest in teaching and service in addition to research
- Experience with at least one of the following research areas:
- Bulk sequencing data (mapping, quantification, down-stream analysis)
- Single cell sequencing analysis (RNA, DNA)
- Analysis of other omics domains (proteomics, lipidomics, metabolomics, etc)
- Analysis of large, complex datasets (clinical records, biological datasets, etc)
- Machine learning approaches
Desirable skills / interests
- Programming skills in R
- Code sharing and collaboration using git/github
- Cloud computing and HPC
- Experience with large biomedical/health record datasets
- Experience with deep learning approaches
Valued personal competencies
- Independent, creative, forward-thinking, and have good decision-making skills
- Outgoing and good with people
- Proficient in English
Expectations as an RA/PhD student
- Carry out an independent research project under supervision
- Write scientific articles and a PhD thesis
- Complete PhD courses / equivalent education corresponding to 30 ECTS points
- Obtain experience with teaching
- Participate in national and international conferences and scientific meetings
- Complete a stay at an external research institution
For further information regarding the position, please contact specialkonsulents Jennifer Bartell ([email protected]) or Thilde Terkelsen ([email protected]). Please apply even if you don’t have experience with any of the ‘desirable skills’ – above all, we are looking for a curious and motivated candidate with a solid computational foundation that they are excited to build on.
Terms of Employment
The successful candidate will be offered a full-time position for a total of 4 years – the first year as research assistant and the following 3 years as PhD student, and employment is governed by the Protocol on PhD Research Fellows signed by the Danish Ministry of Finance and AC (the Danish Confederation of Professional Associations). The transfer to employment as a PhD student after the first year is conditioned upon a positive assessment of the candidate’s research performance during the first year as well as acceptance of enrolment in the Graduate School at the Faculty of Health and Medical Sciences.
How to apply
Your online application must be submitted in English by clicking ‘Apply now’ below. The application must include:
- A short letter describing your background and motivation for applying for this position and the research project
- Curriculum vitae
- Other relevant information such as a list of publications/manuscripts or teaching experience
- Masters diploma (or equivalent) and transcripts of records (including grades)
- References and at least one letter of recommendation
Application deadline: 12 May 2024 at 23:59 CEST.
Please note that only applications submitted before the deadline and consisting of the above listed documents will be considered. Applications will be reviewed on a running basis, and those received after the deadline will not be taken into consideration.
Info
Application deadline: 12-05-2024
Employment start: 05-08-2024
Working hours: Full time
Department/Location: Center for Health Data Science, SUND, KU
Kilde: Jobnet.dk
Information og data
Denne ledige stilling har jobtypen "Øvrige", og befinder sig i kategorien "Øvrige stillinger".
Arbejdsstedet er beliggende i København N.
Jobbet er oprettet på vores service den 16.4.2024, men kan have været deaktiveret og genaktiveret igen.
Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
- Øvrige
- København N
- Søndag den 12. maj 2024
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