Doctoral student in bioinformatics and machine learning

Subject description

At Lund University, we are announcing the position as DDLS PhD student in Data driven evolution and biodiversity

The project aims to understand how codon usage has evolved in organisms, to uncover why and where conservation of codons is central to organismal fitness, and how the three dimensional structures of proteins impact codon choices in coding genes. The recruited doctoral student will develop methods to broadly study patterns of codon usage across organisms and apply large scale evolutionary analysis. A central component of the research will be to develop machine learning and deep learning methods trained on coding sequences and protein structure to extract patterns in data and to draw mechanistic conclusions. The project will involve some experimental evaluation of models in collaboration with researchers at the Linnaeus University. The recruited doctoral student will be enrolled the DDLS research school.

Data driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data Driven Life Science (DDLS) aims to recruit and train the next generation of data driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.3 billion SEK (about 290 MUSD) over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.

In 2025 the DDLS Research School will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ 

Data driven evolution and biodiversity concerns research that takes advantage of the massive data streams offered by techniques such as high-throughput sequencing of genomes and biomes, continuous recording of video and audio in the wild, high-throughput imaging of biological specimens, and large-scale remote monitoring of organisms or habitats. 

The future of life science is data driven. Will you be part of that change?

Then join us in this unique program!

Work duties

The main duties of doctoral students are to devote themselves to their research studies which includes participating in research projects and third cycle courses. The work duties can also include teaching and other departmental duties (no more than 20%).

Admission requirements

A person meets the general admission requirements for third cycle courses and study programmes if the applicant:

• has been awarded a second cycle qualification, or
• has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or
• has acquired substantially equivalent knowledge in some other way in Sweden or abroad.

A person meets the specific admission requirements for third cycle studies in molecular biophysics if the applicant has:

• A minimum of 120 credits are to derive from chemistry courses, including basic courses in biochemistry or cell biology
• At least 30 credits from a second-cycle degree project in the chosen specialization or a closely related specialization.
• In certain cases, the requirement for chemistry courses may be replaced by other subjects. The specific entry requirement may also have been obtained through other equivalent education, which is assessed in each individual case.

Additional requirements:

• Very good oral and written proficiency in English.
• Master’s level studies in a program with good preparation for research and appliction of bioinformatical approaches and machine learning to sequences and molecules. This can be a program in bioinformatics, computational biology, machine learning, molecular biotechnology, computational chemistry, molecular physics, computer science, with sufficent preparation to complete the DDLS graduate school.
• A study background including courses devoted to molecular subjects sufficient to understand the biological background of the project
• Demonstrated ability to write scientific code using programming languages such as python and/or C++.

Assessment criteria

Selection for third cycle studies is based on the student’s potential to profit from such studies. The assessment of potential is made primarily on the basis of academic results from the first and second cycle. Special attention is paid to the following:

1. Knowledge and skills relevant to the thesis project and the subject of study.
2. An assessment of ability to work independently and to formulate and tackle research problems.
3. Written and oral communication skills
4. Other experience relevant to the third cycle studies, e.g. professional experience.

Other assessment criteria:

• Experience of developing deep learning methods or more sophisticated machine learning approaches
• Experience of sequence based bioinformatics and evolutionary models
• The project will involve limited amount of experimental testing of computation models. A willingness to engage in this work is required. Experience in practical work involving cells and DNA is beneficial, but not required.
• An interest in working in an multidisciplinary research environment and collaborating with other members of the research group doing experimental work or focusing on other areas of computational modeling

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant, through his or her experience and skills, is deemed to have the abilities necessary for successfully completing the third cycle programme.

Terms of employment

Only those admitted to third cycle studies may be appointed to a doctoral studentship. Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

Preferred start date September 1, 2025, but no later than October 1, 2025.

Instructions on how to apply

Applications shall be written in English and include a cover letter stating the reasons why you are interested in the position and in what way the research project corresponds to your interests and educational background. The application must also contain a CV, degree certificate or equivalent, and other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.).

Interviews are scheduled to be held June 9-13.