Faculty For Mathematical Sciences and Computational Logic

Track: Mathematical Science & Computational Logic

Location: Sonepat, NCR of Delhi.

Mode: Full Time, On Campus

Programme: B. Tech CS and Data Science

ABOUT US

Rishihood University

Rishihood University (RU) has been established under The Haryana Private Universities (Amendment) Act, 2020 and is empowered to award degree as specified in section 22 of UGC Act, 1956.

Rishihood University is India’s first and only impact university. ‘Impact’ is the living spirit of Rishihood. The purpose of education envisioned by the thought leaders of our civilization and that which has motivated the founders to build Rishihood University is beyond just awarding degrees and jobs. The purpose of education is to achieve the highest potential in a learner i.e., Rishihood. Rishihood University provides a unique mix of globally relevant education that is rooted in Indian ideas, quality education that is affordable, and a multi-disciplinary exposure with cutting edge skills of a specialist. To achieve this outcome, education cannot be limited to within the classrooms. RU is a fully residential campus where living and learning seamlessly integrate throughout the day. RU faculty and learners have an active participation with society, industry, researchers, entrepreneurs, and policy makers. This keeps the learning at RU focused on solving the biggest challenges faced by humanity and prepares our learners for the real world. It is time India builds universities driven by a higher purpose, that have a strong committed board to back it, that redefine the way education is imparted both within and outside the classroom. Rishihood is a bold initiative to fulfill this idea. Hence, we are looking for like-minded founding faculty members at Rishihood University.

About Us

Track | Mathematical Sciences

Foundation Mathematics • Linear Algebra and Statistics • Applied Optimization for Data Science

Most students arrive afraid of math. Not because it is hard, but because nobody ever showed them what it is for. If you have felt the joy of a clean proof and wanted to give that to someone else, if you have ever explained why gradient descent works and watched someone's face change, this role was written for you.

You will join Rishihood as a Faculty who will be responsible for one of the most structurally important tracks in the programme. Mathematics at SASTech is not a prerequisite you power through. It is a language you learn to think in. As you grow into the Track Lead role, you will architect the four year mathematical curriculum, coordinate across the ML and CS Foundations tracks, and mentor junior faculty to teach math the way it was meant to be taught.

Requirements

Key Responsibilities

• Teach Foundation Mathematics, Linear Algebra, Statistics, and Applied Optimization across the four year programme
  
• Design coursework where every concept arrives with a reason, linking calculus to optimization, probability to inference, linear algebra to how neural networks actually work
  
• Run labs where students implement optimization algorithms from scratch in Python or MATLAB, not just run them
  
• Coordinate with the ML and CS track leads to sequence math modules intelligently across semesters
  
• Mentor junior faculty to teach mathematics as a computational, applied discipline rather than a rote one
  

Job Specifications

You should hold an M.Tech, Ph.D., or equivalent in a relevant field. Beyond the degree, here is what we care about.

Technical Depth

• Expert command of linear algebra (vector spaces, SVD, PCA), advanced statistics (Bayesian inference, inferential statistics), and optimization theory (convex optimization, stochastic processes)
  
• Computational fluency in Python (NumPy, SciPy), R, or MATLAB; ability to link every topic to its downstream application in data science, cryptography, or simulation
  

The Person

• A genuine love of mathematics, not just as a tool but as a way of thinking; ability to find the right analogy that makes an abstract concept land
  
• Comfort collaborating across disciplines and intellectual honesty: you model how to find out what you do not yet know
  

Good to Have

• PhD in Applied Mathematics, Statistics, or Computational Sciences with a focus on ML or algorithmic complexity
  
• Published research in mathematical modelling, industry background in quantitative finance, actuarial science, or data science research
  

This job description is not intended to be all-inclusive. The employee may be expected to perform other duties as assigned by the supervisor.