Doctoral Researcher in Computational Biology, Bioinformatics and Machine Learning
- Location
- Luxembourg
- Posted
- 27 Jan 2023
- Closes
- 31 Mar 2023
- Discipline
- Biomedicine
- Job Type
- Researcher
- Employment - Hours
- Full time
- Duration
- Fixed term
- Qualification
- PhD
Doctoral Researcher in Computational Biology, Bioinformatics and Machine Learning
(Valid from 27/01/2023 to 31/03/2023)
Language: English (UK)
Location Belval
Country: Luxembourg
Organisation LCSB
data:
Job Number: UOL05537
Contract Fixed Term Contract
Type:
Duration 36 Month
Schedule Full Time
Type:
Work Hours 40.0 Hours per Week
Expected 01/06/2023
Start Date:
Expected End 31/05/2026
Date:
Job Doctoral Researcher
(internal):
Functions: PhD Candidates
The University | About us...
The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.
The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University focuses among
others on cross-disciplinary research in the areas of Data Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education
ranks the University of Luxembourg #3 worldwide for its “international outlook,” #20 in the Young University Ranking 2021 and among the top 250
universities worldwide.
Within the University, the Luxembourg Centre for Systems Biomedicine (LCSB) is a highly interdisciplinary research centre (IC), integrating experimental
biology and computational biology approaches in order to develop the foundation of a future predictive, preventive and personalized medicine.
Your Role...
We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning analysis of
biomedical data and bioscientific programming for a project on the study of neurological disorders. The candidate should have experience in the
analysis of large-scale biomedical data (omics, clinical or neuroimaging data), using statistical methods, pathway/network analysis or machine
learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on omics, neuroimaging and clinical data to predict
prognostic outcomes of interest (clinical progression, worsening of morphometry and connectivity patterns in brain MRI). This will include
implementing and applying software analysis pipelines and interpreting disease-related data together with experimental and clinical collaborators.
Classification models guided by prior mechanistic knowledge will be built, exploiting the known grouping structures among features in the omics and
neuroimaging data, using dedicated structured learning algorithms. With the help of statistics, machine learning and pathway- and network- and
analyses, the goal is to improve the mechanistic understanding of disease-associated alterations in neurological disorders.
What we expect from you…
* The candidate will have an MSc or equivalent degree in bioinformatics, computational biology, biostatistics, machine learning, or related subject
areas
* Prior experience in large-scale data processing and statistics / machine learning is required
* Previous work and publications in bioinformatics analysis of large-scale biomedical data (e.g. omics, clinical, structural bioinformatics,
neuroimaging data) should be outlined in the CV
* Demonstrated skills and knowledge in omics data analysis, biostatistics, machine learning, pathway and network analysis are highly advantageous
* The candidate should have a cross-disciplinary aptitude, strong organizational and interpersonal skills, and a keen interest in collaborative
biomedical research
* Fluency in oral and written English
In Short...
* Contract Type: Fixed Term Contract 36 Month
* Work Hours: Full Time 40.0 Hours per Week
* Location: Belval
* Internal Title: Doctoral Researcher
* Job Reference: UOL05537
The yearly gross salary for every PhD at the UL is EUR 38028 (full time)
How to apply...
Applications should be submitted online and include:
* A detailed Curriculum Vitae
* Cover letter, including a brief description of past research experience and future interests, as well as the earliest possible starting date
* Copies of degree certificates and transcripts
* Name and contact details of at least two referees
Early application is highly encouraged, as the applications will be processed upon reception. Please apply formally through the HR system. Applications
by email will not be considered.
The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to
gender, and not only, in recruitment and career progression of our staff.
In return you will get…
* Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the “University of
the Greater Region” (UniGR).
* A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site
with excellent infrastructure.
* A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous
non-academic partners such as ministries, local governments, associations, NGOs …
* Find out more about the University
* Addresses, maps & routes to the various sites of the University
Further information...
please contact: Enrico Glaab enrico.glaab@uni.lu
Apply here https://emea3.recruitmentplatform.com/syndicated/private/syd_apply.cfm?ID=PSAFK026203F3VBQB7V7VV4I3&nPostingTargetId=119804&nPostingId=81316
----------------------------------------------------------------------------
DISCLAIMER: This e-mail is confidential and should not be used by anyone who is
not the original intended recipient. If you have received this e-mail in error
please inform the sender and delete it from your mailbox or any other storage
mechanism. Springer Nature Limited does not accept liability for any statements
made which are clearly the sender's own and not expressly made on behalf of
Springer Nature Ltd or one of their agents.
Please note that Springer Nature Limited and their agents and affiliates do not
accept any responsibility for viruses or malware that may be contained in this
e-mail or its attachments and it is your responsibility to scan the e-mail and
attachments (if any).
Springer Nature Limited. Registered office: The Campus, 4 Crinan Street, London,
N1 9XW. Registered Number: 00785998 England.
(Valid from 27/01/2023 to 31/03/2023)
Language: English (UK)
Location Belval
Country: Luxembourg
Organisation LCSB
data:
Job Number: UOL05537
Contract Fixed Term Contract
Type:
Duration 36 Month
Schedule Full Time
Type:
Work Hours 40.0 Hours per Week
Expected 01/06/2023
Start Date:
Expected End 31/05/2026
Date:
Job Doctoral Researcher
(internal):
Functions: PhD Candidates
The University | About us...
The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.
The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University focuses among
others on cross-disciplinary research in the areas of Data Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education
ranks the University of Luxembourg #3 worldwide for its “international outlook,” #20 in the Young University Ranking 2021 and among the top 250
universities worldwide.
Within the University, the Luxembourg Centre for Systems Biomedicine (LCSB) is a highly interdisciplinary research centre (IC), integrating experimental
biology and computational biology approaches in order to develop the foundation of a future predictive, preventive and personalized medicine.
Your Role...
We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning analysis of
biomedical data and bioscientific programming for a project on the study of neurological disorders. The candidate should have experience in the
analysis of large-scale biomedical data (omics, clinical or neuroimaging data), using statistical methods, pathway/network analysis or machine
learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on omics, neuroimaging and clinical data to predict
prognostic outcomes of interest (clinical progression, worsening of morphometry and connectivity patterns in brain MRI). This will include
implementing and applying software analysis pipelines and interpreting disease-related data together with experimental and clinical collaborators.
Classification models guided by prior mechanistic knowledge will be built, exploiting the known grouping structures among features in the omics and
neuroimaging data, using dedicated structured learning algorithms. With the help of statistics, machine learning and pathway- and network- and
analyses, the goal is to improve the mechanistic understanding of disease-associated alterations in neurological disorders.
What we expect from you…
* The candidate will have an MSc or equivalent degree in bioinformatics, computational biology, biostatistics, machine learning, or related subject
areas
* Prior experience in large-scale data processing and statistics / machine learning is required
* Previous work and publications in bioinformatics analysis of large-scale biomedical data (e.g. omics, clinical, structural bioinformatics,
neuroimaging data) should be outlined in the CV
* Demonstrated skills and knowledge in omics data analysis, biostatistics, machine learning, pathway and network analysis are highly advantageous
* The candidate should have a cross-disciplinary aptitude, strong organizational and interpersonal skills, and a keen interest in collaborative
biomedical research
* Fluency in oral and written English
In Short...
* Contract Type: Fixed Term Contract 36 Month
* Work Hours: Full Time 40.0 Hours per Week
* Location: Belval
* Internal Title: Doctoral Researcher
* Job Reference: UOL05537
The yearly gross salary for every PhD at the UL is EUR 38028 (full time)
How to apply...
Applications should be submitted online and include:
* A detailed Curriculum Vitae
* Cover letter, including a brief description of past research experience and future interests, as well as the earliest possible starting date
* Copies of degree certificates and transcripts
* Name and contact details of at least two referees
Early application is highly encouraged, as the applications will be processed upon reception. Please apply formally through the HR system. Applications
by email will not be considered.
The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to
gender, and not only, in recruitment and career progression of our staff.
In return you will get…
* Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the “University of
the Greater Region” (UniGR).
* A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site
with excellent infrastructure.
* A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous
non-academic partners such as ministries, local governments, associations, NGOs …
* Find out more about the University
* Addresses, maps & routes to the various sites of the University
Further information...
please contact: Enrico Glaab enrico.glaab@uni.lu
Apply here https://emea3.recruitmentplatform.com/syndicated/private/syd_apply.cfm?ID=PSAFK026203F3VBQB7V7VV4I3&nPostingTargetId=119804&nPostingId=81316
----------------------------------------------------------------------------
DISCLAIMER: This e-mail is confidential and should not be used by anyone who is
not the original intended recipient. If you have received this e-mail in error
please inform the sender and delete it from your mailbox or any other storage
mechanism. Springer Nature Limited does not accept liability for any statements
made which are clearly the sender's own and not expressly made on behalf of
Springer Nature Ltd or one of their agents.
Please note that Springer Nature Limited and their agents and affiliates do not
accept any responsibility for viruses or malware that may be contained in this
e-mail or its attachments and it is your responsibility to scan the e-mail and
attachments (if any).
Springer Nature Limited. Registered office: The Campus, 4 Crinan Street, London,
N1 9XW. Registered Number: 00785998 England.