REANNOUNCEMENT - Postdoc Position - Federated Machine Learning for Complex Multi-OMICS Data
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Odense M
The Department of Mathematics and Computer Science at the University of Southern Denmark for the Computational Biology laboratory chaired by Professor Richard Röttger invites applications for a postdoctoral position within the field of federated machine learning and AI to be filled as soon as possible, for a period of initially 12 months with the prospects of being prolonged. Application deadline: 31 March 2023.
The research is part of a large European effort, FeatureCloud, to establish privacy-aware federated machine learning approaches to enable the mining of distributed, sensitive data. Currently, one major roadblock of biomedical research is that the valuable data is scattered around the globe, and sharing, and consolidating, data is simply not possible due to privacy concerns. With FeatureCloud, we are seeking to elevate this prohibitive problem by allowing federated machine learning, i.e. we leave the data in the safe harbour of storage and train local models at the sites; thereafter only the model parameters are consolidated in a central instance to create a model of similar capabilities as a conventional model trained on all the available data.
The successful candidate will develop novel approaches for federated machine learning of systems medicine and multi-OMICS data in particular. The candidate will be embedded in a highly international and powerful consortium as a member of the Computational Biology group which offers a wide expertise in machine learning on biomedical data, both in the realm of unsupervised as well as supervised learning. We also provide the candidate with direct access to state-of-the-art computing facilities optimized for deep learning and distributed computing.
We are seeking outstanding candidates with strong analytical and problem-solving skills, who are strong in written and oral communication (in English), and have documented experience in data science, machine learning and software development of complex systems. Expertise in the analysis of biological data is an advantage, but not a requirement. Expertise in computer security and data privacy are welcome, but not required.
Place of work:
Computational Biology Group (Professor Richard Röttger, [email protected]), Department of Mathematics and Computer Science, located at the main campus of the University of Southern Denmark, Odense, Denmark.
Application, salary etc.
The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary and taxation.
Application must be made in the form of a Declaration of Interest and must include the following documents:
1. Letter of motivation and proposed project description, outlining the candidate’s ideas of how to approach the project (max. two pages).
2. Curriculum vitae, including information on previous employment, list of programming skills mastered by the applicant, and teaching and supervision experience.
3. A list of publications stating the scientific publication(s) on which the applicant wishes to rely (if available).
4. A certified copy of your PhD degree certificate
5. At least one letter of recommendation from supervisors or previous employers.
Shortlisting may be used in the assessment process.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated.
To qualify you must have passed a PhD or equivalent. Applications will be assessed by an expert assessor/committee. Applicants will be informed of their assessment by the university.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Applications must be submitted electronically using the link "Apply online". Attached files must be in Adobe PDF or Word format. Each box can only contain a single file of max. 10 Mb. We strongly recommend that you read How to apply before you apply.
Further information for international applicants about entering and working in Denmark.
The research is part of a large European effort, FeatureCloud, to establish privacy-aware federated machine learning approaches to enable the mining of distributed, sensitive data. Currently, one major roadblock of biomedical research is that the valuable data is scattered around the globe, and sharing, and consolidating, data is simply not possible due to privacy concerns. With FeatureCloud, we are seeking to elevate this prohibitive problem by allowing federated machine learning, i.e. we leave the data in the safe harbour of storage and train local models at the sites; thereafter only the model parameters are consolidated in a central instance to create a model of similar capabilities as a conventional model trained on all the available data.
The successful candidate will develop novel approaches for federated machine learning of systems medicine and multi-OMICS data in particular. The candidate will be embedded in a highly international and powerful consortium as a member of the Computational Biology group which offers a wide expertise in machine learning on biomedical data, both in the realm of unsupervised as well as supervised learning. We also provide the candidate with direct access to state-of-the-art computing facilities optimized for deep learning and distributed computing.
We are seeking outstanding candidates with strong analytical and problem-solving skills, who are strong in written and oral communication (in English), and have documented experience in data science, machine learning and software development of complex systems. Expertise in the analysis of biological data is an advantage, but not a requirement. Expertise in computer security and data privacy are welcome, but not required.
Place of work:
Computational Biology Group (Professor Richard Röttger, [email protected]), Department of Mathematics and Computer Science, located at the main campus of the University of Southern Denmark, Odense, Denmark.
Application, salary etc.
The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary and taxation.
Application must be made in the form of a Declaration of Interest and must include the following documents:
1. Letter of motivation and proposed project description, outlining the candidate’s ideas of how to approach the project (max. two pages).
2. Curriculum vitae, including information on previous employment, list of programming skills mastered by the applicant, and teaching and supervision experience.
3. A list of publications stating the scientific publication(s) on which the applicant wishes to rely (if available).
4. A certified copy of your PhD degree certificate
5. At least one letter of recommendation from supervisors or previous employers.
Shortlisting may be used in the assessment process.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated.
To qualify you must have passed a PhD or equivalent. Applications will be assessed by an expert assessor/committee. Applicants will be informed of their assessment by the university.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Applications must be submitted electronically using the link "Apply online". Attached files must be in Adobe PDF or Word format. Each box can only contain a single file of max. 10 Mb. We strongly recommend that you read How to apply before you apply.
Further information for international applicants about entering and working in Denmark.
Information og data
Denne ledige stilling har jobtypen "Forsker", og befinder sig i kategorien "Sundhed og forskning".
Arbejdsstedet er beliggende i Odense M.
Jobbet er oprettet på vores service den 16.1.2023, 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.
- Forsker
- Odense M
- Fredag den 31. marts 2023
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