Job Title: Intern - SMB Crystallography

SLAC Job Postings

Position Overview:

The Stanford Synchrotron Radiation Light Source (SSRL) Directorate at SLAC National Accelerator Laboratory is seeking a research Intern with interest in biology, physics, computer science and mathematics to join as a member of the Structural and Molecular Biology department. SSRL is a facility where small wavelength radiation (~1 Angstrom X-rays) is produced to allow scientists to explore the atomic world. Our group specializes in protein crystallography, where researchers bring crystalline samples of biologically important proteins and use the X-rays to gain insights into the atomic-level structure of the proteins. This kind of information is crucial for the field of drug design, where disease-relevant proteins can be rendered useless by small drug molecules (called ligands). The intern will join our team during a critical time as we build a new facility dedicated to bio preparedness with an emphasis on structure driven drug design. The internship will be 100% computational, and the intern will work closely with our data processing and algorithms team who are writing new code to support the newly proposed drug design resource. Current projects include training and using machine learning models to auto-classify microscope images of crystalline samples grown in our labs, as well as locating the crystals so they can later be optimally positioned in the X-rays. This work needs to be fully automated, and the results need to be streamed to a smart database where users can maintain easy access. This is one of many projects the team is working on, and the intern will gain familiarity with other tasks, should time permit.

Your specific responsibilities include (but are not limited to): Use existing image segmentation models (e.g. SAM https://segment-anything.com/ ) to extract important features in images of crystal plates containing multiple sample droplets referred to as "wells". Train an AI model using PyTorch to accurately label each sample "well", for example "contains crystal" or "empty", etc. For each "well" that contains crystals, design an image processing algorithm to accurately locate the crystals, storing that information for downstream use. Opportunities and Benefits: Learn coding in Python. Become proficient working in Linux and BASH. Learn code versioning with Github. Learn job scheduling with SLURM, working on compute clusters, and using GPUs. Learn parallel programming using MPI (Message-Passing-Interface). Learn how to train machine learning models using PyTorch. Learn about Protein crystallography. Collaborate with other interns in the SMB group. Come to California and experience life in the Bay area. Discover what a career might be like working in the national lab setting, somewhere in between academia and industry. Note: This is an hourly, non-benefits eligible temporary-nonexempt student position (work at 50% full-time equivalent or more), not to exceed 980 hours in six consecutive months Eligible applicants must be at least 18 years of age, currently enrolled in an educational program or recently graduated, and have US work authorization.

To be successful in this position you will bring (some if not all): A strong work ethic, previous work experience is desired (anywhere, high school jobs count). A coursework history in sciences (Bio, Chem, Physics, Math, CompSci) or related An enjoyment of Mathematics, and coursework through intermediate Calculus. A desire to learn computer programming, even if you have no experience. A curiosity about nature at the atomic level. A willingness to spend time problem solving. A willingness to give talks and updates in a group setting. An interest in image processing and convolutional neural networks for image classification. SLAC Employee Competencies : Effective Decisions: Uses job knowledge and solid judgment to make quality decisions in a timely manner. Self-Development: Pursues a variety of venues and opportunities to continue learning and developing. Dependability: Can be counted on to deliver results with a sense of personal responsibility for expected outcomes. Initiative: Pursues work and interactions proactively with optimism, positive energy, and motivation to move things forward. Adaptability: Flexes as needed when change occurs, maintains an open outlook while adjusting and accommodating changes. Communication: Ensures effective information flow to various audiences and creates and delivers clear, appropriate written, spoken, presented messages. Relationships: Builds relationships to foster trust, collaboration, and a positive climate to achieve common goals. Physical requirements and Working conditions: Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job. Work standards: Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations. Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for environment, safety and security; communicates related concerns; uses and promotes safe behaviors based on training and lessons learned. Meets the applicable roles and responsibilities as described in the ESH Manual, Chapter 1-General Policy andResponsibilities:http://wwwgroup.slac.stanford.edu/esh/eshmanual/pdfs/ESHch01.pdf Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu ------------------------------------------- Classification Title : SLAC Intern Students [Level II] Job code : 0901 Employment Duration : Temporary
The expected pay range for this position is $24.26 - $26.25. per hour. SLAC National Accelerator Laboratory/Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.