Jobid=018cdebe8d5b (0.0143)
ph3Job Overview /h3 pWe seek a highly-motivated postdoctoral researcher to develop advanced computational methods for cryogenic electron tomography (cryo‑ET) that enable the visualization of molecular complexes directly within cells. The role focuses on developing improved image‑simulation frameworks, guiding experimental design, and creating computational strategies that combine physics‑based modeling, optimisation, and machine learning to enhance cryo‑ET image‑processing workflows, including tilt‑series alignment, 3D template matching, particle detection, and quantitative tomogram interpretation. /p pYour home base will be the Jakobi Lab at TU Delft, part of the Kavli Institute of Nanoscience. The team is multidisciplinary and internationally diverse, and you will have opportunities to mentor students and contribute to cutting‑edge research in a collaborative environment. /p h3Responsibilities /h3 ul liDevelop and implement advanced computational methods for cryo‑ET image simulation and processing. /li liTranslate simulation insights into experimental design and optimisation of molecular probes for specific target complexes. /li liCombine physics‑based modeling, optimisation techniques, and machine learning to improve cryo‑ET workflows. /li liSupport ongoing projects by building image‑processing pipelines, performing data interpretation, and ensuring methodological advances facilitate biological discovery. /li /ul h3Qualifications /h3 ul liPhD in computational science, physics, applied mathematics, bioinformatics, structural biology, or a related field. /li liStrong computational and programming skills in languages such as Python, Julia, or C++ with experience in scientific computing, machine learning libraries, and high‑performance computing. /li liExperience with image analysis or computational imaging, ideally in electron microscopy, tomography, or related modalities. /li liDemonstrated experience developing algorithms or computational methods (e.g., image simulation, optimisation, data‑analysis workflows). /li liInterest or experience with machine learning approaches for scientific data analysis. /li liStrong interdisciplinary collaboration skills and enthusiasm for working with experimental scientists. /li liClear and effective communication in English. /li /ul h3Preferred Qualifications /h3 ul liExperience with cryo‑EM or cryo‑ET data analysis, including tilt‑series alignment, 2D/3D template matching, or subtomogram averaging. /li liExperience with physics‑based modelling or simulation of imaging processes. /li liFamiliarity with scientific software development. /li liA track record of peer‑reviewed publications demonstrating methodological or computational contributions. /li /ul h3Conditions of Employment /h3 ul liDuration of contract is 2 years. Temporary. /li liA job of 38 hours per week. /li liSalary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. /li liAn excellent pension scheme via the ABP. /li liThe possibility to compile an individual employment package every year. /li liDiscount with health insurers on supplemental packages. /li liFlexible working week. /li liEvery year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget. /li liPlenty of opportunities for education, training and courses. /li liPartially paid parental leave. /li liAttention for working healthy and energetically with the vitality program. /li /ul /p #J-18808-Ljbffr
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