PhD student in Machine Learning

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We are looking for a PhD student in Machine Learning.

The research focus for the advertised position is machine learning for forensic science. The project involves development of novel probabilistic and deep learning models for answering various forensic questions such as estimating time of death, inferring causes of death, or finding metabolomic fingerprints. The modelling process will require extending and combining multiple frameworks in deep learning (such as variational autoencoders, convolutional neural networks), statistical models (such as state-space models), scientific machine learning (e.g. combining deep learning with differential equations) and interpretable machine learning. The project involves both fundamental research on new machine learning models and computational algorithms, as well as applied research to demonstrate the usefulness of the new methods in solving real world problems in the forensic field. The PhD project will be carried out in collaboration with the National Board of Forensic Medicine (RMV). Machine learning has made a significant impact during the past few years in medical applications that use similar kinds of data (metabolomics), and in the forensic field there is the possibility that machine learning and metabolomics will have a huge impact. The advertised PhD project will contribute to this positive development.

The position is a part of the project How to solve murders using postmortem metabolomic fingerprints and artificial intelligence , funded by the Swedish Research Council. The project includes researchers from multiple fields such as forensic sciences, system biology and machine learning, and this PhD position assumes strong interdisciplinary collaboration between the PhD student and other researchers in the project.

As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time.

N.B. When applying for the position we want you to provide a personal letter (first field in the application form). This letter should contain a paragraph where you briefly explain/list the qualifications that you believe are particularly relevant for the research topic described above. This paragraph should start with the words “Suitability for research topic:”.

You have a master’s degree in machine learning, statistics, computer science, or a related area that is considered relevant for the research topic of the project, or have completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in the subject areas mentioned above. Alternatively, you have gained essentially corresponding knowledge in another way.

A successful candidate should have excellent study results. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. It is also desirable that the applicant has a strong background in mathematics and statistics. The applicant should furthermore have a strong drive towards solving real world problems by doing fundamental research; the ability and interest to work collaboratively; and strong communication skills. The applicant should be able to communicate freely in oral and written English. Since the project will work with sensitive data, the applicant profiles will go through an internal RMV screening as the first selection step.

Linköping University is one of the leading AI institutions in Sweden, and researchers in the project have links to various prominent national AI initiatives and steering groups, such WASP and AI commission.

National Board of Forensic Medicine (RMV) is an expert authority within the Swedish judiciary that works with forensic investigations on behalf of the police, prosecutors, courts and correctional services. This PhD project is connected to the department of forensic genetics and forensic toxicology.

The position is formally based at the Division of Statistics and Machine Learning (STIMA). At STIMA we conduct research and education in both statistics and machine learning, at the undergraduate, advanced and PhD levels. STIMA is characterized by a modern view of the statistical subject, where probabilistic models are combined with computational algorithms to solve challenging complex problems, as well as a statistical view of machine learning which clearly integrates the two subject areas within the division. For more information about STIMA, please see https://liu.se/en/organisation/liu/ida/stima

STIMA is part of the Department of Computer and Information Science (IDA) – a dynamic, international, and collaborative environment with a strong focus on research, which spans the range from purely theoretical to applied, where the latter is often being conducted in cooperation with industrial partners and other organizations. The department consists of five divisions, covering most areas of computer and information science. For further information about the department, please see https://liu.se/en/organisation/liu/ida

When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University

The employment has a duration of four years’ full-time equivalent. You will initially be employed for a period of one year. The employment will subsequently be renewed for periods of maximum duration two years, depending on your progress through the study plan. The employment may be extended up to a maximum of five years, based on the amount of teaching and departmental duties you have carried out. Further extensions can be granted in special circumstances.

Starting date by agreement. 

The salary of PhD students is determined according to a locally negotiated salary progression.

More information about employment benefits at Linköping University is available here.

Information about union representatives, see Help for applicants .

Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than April 23, 2024.

Applications and documents received after the date above will not be considered.

We welcome applicants with different backgrounds, experiences and perspectives - diversity enriches our work and helps us grow. Preserving everybody's equal value, rights and opportunities is a natural part of who we are. Read more about our work with: Equal opportunities .

We look forward to receiving your application!

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