Screen4Care: PhD Position for Developing a Federated Database for Clinical Data
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Odense M
The Department of Mathematics and Computer Science, SDU for the Computational Biology group chaired by Professor Richard Röttger invites applications for a PhD position for the creation of a federated metadata platform for sensitive clinical data, to be filled as soon as possible.
A large roadblock of medical research is the difficult access to sensitive data which therefore hinders the training of complex and powerful machine learning models. This issue is amplified when considering rare diseases with low incidence numbers per clinic. To enable the identification of suitable patients for clinical studies amenable to machine learning, a privacy-preserving metadata platform is required. Here, the actual patient data remains at the site of storage, for instance the hospital, but virtual cohorts can be identified according to clinical phenotypes, symptoms and diagnoses, and later used for federated machine learning approaches without breaching patient privacy.
The position itself is part of the large European endeavour Screen4Care, funded by the Innovative Medicines Initiative in a public/private partnership between numerous, high-profile research institutes and the European Federation of Pharmaceutical Industries and Associations. The overall vision of Screen4Care is to shorten the path to rare disease diagnosis; the envisioned metadata repository is one key aspect of fulfilling this vision. The selected candidate will gather research as well as industrial experience by the close collaboration of SDU and the EFPIA partners.
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 the development of complex compute systems.
The applicant should be fluent in the state-of-the-art web-development frameworks, virtualization techniques as well as database technologies.
Expertise in clinical data science and machine learning as well as computer security and data privacy is welcome.
This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 101034427. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
For further information please contact Professor Richard Röttger, tel.: +45 6550 2337, e-mail: [email protected].
Application, salary etc.
Appointment as a PhD Research Fellow is for three years. Employment stops automatically at the end of the period. The holder of the scholarship is not allowed to have other paid employment during the three-year period.
The successful applicant will be employed in accordance with the agreement on salaried PhD scholars between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary and taxation.
The successful candidate will be enrolled at this university in accordance with faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order).
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Application must be in English and made in the form of a Declaration of Interest including the following:
• A research proposal/description of your approach to the above project (max one page excluding references)
• A letter stating your specific interest, motivation and qualifications for the project in question (max. two pages) (please attach this under box "Application form")
• Detailed CV, including personal contact information
• Copies of diplomas, Bachelor as well as Master’s degree, including transcript of notes/grades
• At least two signed reference letters. Should your referees wish to send their letters directly to us, please have them use e-mail: [email protected] mentioning your name and the title of the position in the subject line. And please note that these also need to reach us before deadline.
Shortlisting may be used in the assessment process.
Further information about the PhD-study can be found at the homepage of the University.
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.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters.
Further information for international applicants about entering and working in Denmark.
A large roadblock of medical research is the difficult access to sensitive data which therefore hinders the training of complex and powerful machine learning models. This issue is amplified when considering rare diseases with low incidence numbers per clinic. To enable the identification of suitable patients for clinical studies amenable to machine learning, a privacy-preserving metadata platform is required. Here, the actual patient data remains at the site of storage, for instance the hospital, but virtual cohorts can be identified according to clinical phenotypes, symptoms and diagnoses, and later used for federated machine learning approaches without breaching patient privacy.
The position itself is part of the large European endeavour Screen4Care, funded by the Innovative Medicines Initiative in a public/private partnership between numerous, high-profile research institutes and the European Federation of Pharmaceutical Industries and Associations. The overall vision of Screen4Care is to shorten the path to rare disease diagnosis; the envisioned metadata repository is one key aspect of fulfilling this vision. The selected candidate will gather research as well as industrial experience by the close collaboration of SDU and the EFPIA partners.
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 the development of complex compute systems.
The applicant should be fluent in the state-of-the-art web-development frameworks, virtualization techniques as well as database technologies.
Expertise in clinical data science and machine learning as well as computer security and data privacy is welcome.
This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 101034427. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
For further information please contact Professor Richard Röttger, tel.: +45 6550 2337, e-mail: [email protected].
Application, salary etc.
Appointment as a PhD Research Fellow is for three years. Employment stops automatically at the end of the period. The holder of the scholarship is not allowed to have other paid employment during the three-year period.
The successful applicant will be employed in accordance with the agreement on salaried PhD scholars between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary and taxation.
The successful candidate will be enrolled at this university in accordance with faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order).
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Application must be in English and made in the form of a Declaration of Interest including the following:
• A research proposal/description of your approach to the above project (max one page excluding references)
• A letter stating your specific interest, motivation and qualifications for the project in question (max. two pages) (please attach this under box "Application form")
• Detailed CV, including personal contact information
• Copies of diplomas, Bachelor as well as Master’s degree, including transcript of notes/grades
• At least two signed reference letters. Should your referees wish to send their letters directly to us, please have them use e-mail: [email protected] mentioning your name and the title of the position in the subject line. And please note that these also need to reach us before deadline.
Shortlisting may be used in the assessment process.
Further information about the PhD-study can be found at the homepage of the University.
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.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters.
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 14.10.2023, 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 24. november 2023
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