What is Data-driven Life Science?

Data-driven life science is a field of research that focuses on using data, computational methods and artificial intelligence to study biological systems and processes. This approach can include assembling, sharing, integration and advanced analysis of large amounts of data from diverse sources, including experiments, observations, and simulations, in order to gain a better understanding of how living organisms function.

For a PhD project to be considered data-driven it has to have a clear data science component such as the use of advanced data analysis techniques, from statistics to machine learning involving either method development or novel application of data science methods to life science problems. Projects that only involve laboratory research or that depend solely on the acquisition of large amounts of new biological data from e.g. laboratory experiments or patient materials will not be given priority. However, laboratory research to validate and extend data-driven insights can be included.

Role of the DDLS Research School

The focus of the research school is to engage the students with a national network and in annual network activities. The DDLS Research School will complement already existing graduate school and other training activities at universities, and it does not represent a full standalone national PhD training program. Specific national DDLS Research School courses will be provided at a national to assure that the students will at the end of their education have proficiency in data handling and analysis, integration of multidisciplinary knowledge and ethics.

The supervisors of the DDLS PhD students are expected to be active in organizing and contributing course material and training events of the DDLS Research School. The students will also have access to a plethora of other training and courses arranged by the SciLifeLab Training Hub.

Requirements

Project proposals in the four DDLS research areas are welcome. The funded projects should be in line with DDLS strategy and have a novel and original data-driven perspective, be of high scientific quality and combine the life science and data science topics. Project applicant, i.e. the main supervisor of the PhD student must have a secured employment at a Swedish University during the suggested PhD period.

The call is open to all researchers in Sweden who can act as a main supervisor or a co-supervisor for a PhD student. One applicant can be the main supervisor in only one academic and one industrial project, but can act as co-supervisors in applications by other PIs. DDLS fellows who already have a start-up package with PhD student positions, cannot apply to the call as main supervisor for DDLS academic PhD student positions. However, they can file joint applications as co-supervisor together with e.g. SciLifeLab, WCMM fellows or any other scientists with the goal of forming new joint collaborations and creating new multi-disciplinary data-driven opportunities for training PhD students.

Project participants (supervisors and students) are expected to be active contributors and participants in the national DDLS community events, training activities, seminars, and symposia organized by the DDLS Research School.

Any necessary co-funding needed for a KAW-funded project is the responsibility of each university/ department /PI and should be ensured via a letter of commitment from the head of the department/faculty.

Required Documents

• Letter of commitment from the Head of Department/faculty
• CV of the suggested main supervisor (max 2 pages + 1 page Top 10 publications)
• CV of the co-supervisor(s) (if applicable) (1 page CV)
• Research project proposal: Up to three pages. Describe the field of research and the central questions, include the specific aims of the suggested PhD project, the material and methods and data analysis and computational approaches as well as the contributions from the team of supervisors. Indicate what additional costs are encountered in the project and how such costs will be covered from other funding sources. Explain the training plan for the PhD student. Indicate why this project and the PI and the co-PIs are ideal to promote the goals of the DDLS and the specific DDLS research area, both in terms of research questions and the training of next-generation life scientists.
• Description of the research and training environment
  • 1 page, including the following: what is the local research environment of the PI (laboratory, department, faculty, university) and how this links to the DDLS program goals and provides a good training environment with sufficient critical mass of expertise. Describe how the team of supervisors will collaborate. Describe any local graduate school/doctoral program the student will be affiliated with and how this could provide synergistic benefits.

Evaluation Process and Decisions

Project proposals and PIs are evaluated and ranked by international reviewers. Projects are evaluated according to defined DDLS evaluation criteria:

• Scientific quality of the project
• Merits of the applicant and co-applicants supervisor/co-supervisor (scientific and training)
• Fit and contribution of the project to the DDLS program
• Quality of the supervision plan and the training environment

We will also consider inclusiveness and diversity.

Decisions

The projects will first be screened for eligibility, and then sent to an international evaluation committee. Initially, the plan was for the DDLS Steering Group to assess the projects after the pre-screening process. Since conflicts of interest emerged for some of the Steering Group members, the group is no longer part of the evaluation process. The final decisions will be made by the SciLifeLab National Board. We will select about 20 projects, as well as a few backup projects. As we expect a very large number of applications, we are not able to provide detailed written feedback on each application. The accepted supervisor(s) are then eligible to be part in the next step, the selection of the PhD students as part of an international call. The supervisors(s) are then also invited to take part in the activities of the DDLS program, the DDLS Research School and contribute to associated training events.

The next steps in the process will be refined later on, but are described here for completeness.

PhD Student Selection: International Announcement of All Positions

After the board decision is done, SciLifeLab will coordinate an international joint announcement for all DDLS PhD positions. This will be done jointly together with all DDLS partner organizations that have been granted a PhD slot. The announcement will be posted in relevant major international sites, and includes a short description of the DDLS program and

the four DDLS research areas, information onthe positions at each university, a short description of each of the project and the associated PIs (affiliation, research area, website), desired skills and qualifications of the candidates as well as any specific requirements of the host graduate school. The details will be available via links to the SciLifeLab web site and local sites.

Each university with a granted project can also announce the position at their respective websites to meet the local rules and regulations. The local announcement should clearly indicate that the PhD position is part of a large national DDLS program.

Application Process and Requirements for the PhD students

The PhD student candidates will submit their applications to the respective university, according to the local application instructions. The candidates can apply to multiple positions but will need to file an application separately at each university.

Required documents should include any documents typically required by the respective university, including a detailed description of the motivation, track-record and potential of the candidate in data-driven life science.

Evaluation of the PhD Candidates

All PIs with approved projects select their PhD candidates from the international joint PhD call according to the timelines set by the DDLS program. The purpose of the joint timelines is to promote the national aspect of the program.

During the recruitment process at each local department with granted PIs, a DDLS representative is recommended to be present at the interviews but they will not participate in the scoring and selection of the candidates.

The role of the DDLS representative is only to ensure that the candidates from the international search are fairly considered and meet the overall requirements of the DDLS program and the DDLS research school. If the DDLS representative cannot be part of the committee, a one-page description of the selection process, including a summary of the main applicants from the international call is requested by the DDLS office. All the selected candidates are at this stage approved by the DDLS Program Director and are eligible for funding.

Conditions for Funding

The DDLS program finances both 4-year full-time PhD positions as well as positions for 5 years at an 80% effort. It is currently expected that 20 projects / PhD positions in academia will be awarded in the first round of the recruitment. The PIs of the approved projects, together with the head of department, will be asked to sign an agreement containing the Terms and Conditions of the suggested DDLS funding. The granted funds will not be available until the PhD student is recruited by the department/university. The incurred project costs will be requisitioned according to the funding conditions for all DDLS activities.

Financial Information

• The grants will be funded by KAW. The PIs, departments or faculties are responsible for any necessary co-funding needed at each university.
• 3,25 MSEK total KAW funding per project.
• Out of the total KAW funding, max. 165 KSEK can be allocated for running costs during the project period defined.
• A maximum of 18% of the amount granted by KAW can be allocated for premises and overhead costs.
• There is also a maximum coverage of 50% for LKP (payroll overhead) on personnel costs.
• Costs will be reimbursed by requisition to KAW. KTH/SciLifeLab will coordinate this process. Information about the financial process flow and reporting templates will be provided for this purpose at a later stage.
• No funding can be directed to industry, industrial partners or other public sectors in this call.