Postdoctoral researcher in data-driven, multimodal modeling of neurodegenerative disease - Hiring in process/Finished, not possible to apply

Description of the workplace

The research group for Clinical Memory Research, led by Oskar Hansson, conducts research in dementia. The research includes animal- and cell biology experiments, and works with cohorts of patients undergoing extensive neuroimaging, biomarker measurements and neuropsychological testing. The postdoctoral researcher will join a growing multidisciplinary team of neuroscientists and clinical researchers who are dedicated to increasing our collective understanding about neurodegenerative diseases. More information can be found here.

The postdoctoral researcher will be working in Jacob Vogel’s lab, which is part of the research group. Our research uses data-driven approaches to model biological processes marking the onset and progression of neurodegenerative diseases, such as Alzheimer’s disease, Lewy body dementias, and frontotemporal dementia spectrum disorders. We specialize in various statistical learning approaches, which we apply to large datasets combining neuroimaging, genomic, and other multi-omic data. The long-term goal of our research is to contribute to the development of new treatments for neurodegenerative diseases, where clinically meaningful treatments are still lacking.

We are committed to creating a positive, respectful and stimulating environment. We value communication and collaboration, and we strive for a workplace that promotes learning and development of all employees. We are also committed to building a safe and positive environment for all employees through mutual respect and toleration. This position will be placed at BMC in Lund, Sweden.

Research area

While our lab is involved in a wide range of different pursuits, our principal research aims focus on the i) resolving disease heterogeneity, ii) charting disease-associated molecular changes, iii) using statistical learning to forecasting disease outcomes, and iv) studying indices of disease vulnerability and resilience across the lifespan. We pursue these aims by integrating data across several large and deeply phenotyped public and private datasets that include multi-omic, neuroimaging (PET, MRI, fMRI, DWI), cognitive, neuropathology, and in vivo (cerebrospinal fluid) data, often in the same individuals.

Work duties and areas or responsibilities

As a postdoctoral researcher you will primarily participate in data analysis as it pertains to research foci described above. The exact project will be decided with your input in an attempt to tailor the project focus to your interests and skillset. Other work responsibilities may include: data curation and processing; composition, editing, or executing of computational scripts; presenting data and findings at internal and external research meetings; composition of scientific manuscripts; informal mentorship of and skill-sharing with other employees; and/or composition of grants and/or research fellowships. Other work duties may also occur.

Eligibility

Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position. This eligibility requirement needs to be met no later than the time when the employment decision is made. We will mainly consider candidates who have completed their PhD degree no more than three (3) years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier. These circumstances refer to leave due to illness, parental leave, clinical work, positions of trust within trade union organizations or other similar circumstances.

Basis for assessment

At Lund University, employment as a postdoctoral researcher provides opportunities for scientific and pedagogical merit. There is mainly room for merit in research, but also for certain higher education pedagogical training. Teaching may be included in the tasks.

For the employment as a postdoctoral research, scientific ability will primarily be taken into account.

Other qualifications

The following are also required for the position:

• Ph.D. in engineering, neuroscience, statistics, quantitative biology, physics, mathematics or a related discipline;
• Fluency in computational programming, preferably using python or R
• Familiarity and experience with high-performance cluster-based computing
• Expertise in statistical modeling
• Ability to independently perform large-scale data analyses
• Excellent communications skills in English, both verbal and written
• A proven track record of research productivity
• Candidate should be thorough, detail-oriented, and should demonstrate an intrinsic motivation for research into neurodegenerative diseases

The following are considered to be a merit:

• Research experience in the field of neurodegenerative disease
• Experience with curation, preprocessing and/or analysis of neuroimaging, genomic, or other types of omics data
• Familiarity with git and GitHub and/or Datalad
• Expertise in statistical learning approaches (e.g. machine learning, deep learning)
• Familiarity with best practices in reproducibility and open science
• Individuals from diverse or underrepresented backgrounds are encouraged to apply

Terms of employment
This is a full-time employment limited to 2 years with preliminary start date on or after 1st of February 2023, or according to agreement. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral researcher”) between SACO-S, OFR/S and SEKO, dated November 19, 2021. Extension of position up to an additional year may be possible.

Application

Applications must include a personal motivation letter, a CV, contact information of three references, a diploma and other documents you wish to be considered (e.g. letters of recommendation). If your diploma has not yet been issued when you apply for the position, please send it in afterwards via e-mail to Linnea Gard (linnea.gard@med.lu.se).