Post Doctoral Associate

About the role

The Kaelber lab located in the Department of Molecular Biology and Biochemistry on Rutgers’ Busch Campus, within walking distance of research buildings for computer science and medicine as well as fundamental biology is searching for a Post Doctoral Associate. Prof. Kaelber is the 3DEM Advisor to the RCSB PDB (Protein Data Bank). The postdoctoral associate will attend relevant seminar series on this and other campuses of Rutgers related to origins of life research, artificial intelligence methods development, evolutionary biology, and computational biology. Prof. Kaelber is recruiting a “dry lab” scientist for methods development in evolutionary biology. The postdoctoral associate will develop and benchmark methods for evolutionary analysis by the comparison of protein structures, conduct rigorous evaluations of the concordance of computational results to validation sets, and then determine the origin of life on earth. Mentorship of 1-2 undergraduate students will be encouraged. The postdoctoral associate will collaborate with “wet lab” experimentalists in the research group and with interdisciplinary collaborating scientists. Elements of the experimental approach will include: Bayesian reconstruction of events on billion-year timescales, determination of optimal embeddings and encodings for protein structures, multiple structural alignments, relevant artificial intelligence (AI) approaches such as CNNs and transformers, and protein structure predictions.

Responsibilities

• Develop and benchmark methods for evolutionary analysis by the comparison of protein structures
• Conduct rigorous evaluations of the concordance of computational results to validation sets
• Determine the origin of life on earth
• Mentor 1-2 undergraduate students
• Collaborate with wet‑lab experimentalists in the research group and with interdisciplinary collaborating scientists
• Apply Bayesian reconstruction of events on billion‑year timescales
• Determine optimal embeddings and encodings for protein structures
• Perform multiple structural alignments
• Utilize relevant artificial intelligence approaches such as CNNs and transformers
• Generate protein structure predictions

Requirements

Minimum Education and Experience: Ph.D. in life sciences, chemical sciences or other related field.

Required Knowledge, Skills, and Abilities: Excellence in at least two of the following: structural biology, programming and high‑performance computing, bioinformatics or evolutionary theory. Required skills: commitment to ethical conduct of research, self‑motivation and independence, good documentation habits, and a track record of productive scientific results.

Equipment Utilized: High‑performance computing; cloud computing; local workstations.

Physical Demands and Work Environment: Work will be performed in an office setting. Applicants must be physically capable of interfacing with computers at a swift rate.

Benefits

• Medical, prescription drug, and dental coverage
• Paid vacation, holidays, and various leave programs
• Competitive retirement benefits, including defined contribution plans and voluntary tax‑deferred savings options
• Employee and dependent educational benefits (when applicable)
• Life insurance coverage
• Employee discount programs

Pay

The salary range for this position is $63,968–$75,564. The final salary offer may be determined by several factors, including the candidate’s qualifications, experience, and expertise, and availability of department or grant funds to support the position. Market benchmarks and internal equity are also considered to ensure fair compensation relative to the university’s broader compensation structure.